idx int64 1 56k | question stringlengths 15 155 | answer stringlengths 2 29.2k ⌀ | question_cut stringlengths 15 100 | answer_cut stringlengths 2 200 ⌀ | conversation stringlengths 47 29.3k | conversation_cut stringlengths 47 301 |
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9,701 | What R packages do you find most useful in your daily work? | Packages I often use are raster, sp, spatstat, vegan and splancs. I sometimes use ggplot2, tcltk and lattice. | What R packages do you find most useful in your daily work? | Packages I often use are raster, sp, spatstat, vegan and splancs. I sometimes use ggplot2, tcltk and lattice. | What R packages do you find most useful in your daily work?
Packages I often use are raster, sp, spatstat, vegan and splancs. I sometimes use ggplot2, tcltk and lattice. | What R packages do you find most useful in your daily work?
Packages I often use are raster, sp, spatstat, vegan and splancs. I sometimes use ggplot2, tcltk and lattice. |
9,702 | What R packages do you find most useful in your daily work? | For me personally, I use the following three packages the most, all available from the awesome Omega Project for Statistical Computing (I do not claim to be an expert, but for my purposes they are very easy to use):
RCurl: It has lots of options which allows access to websites that the default functions in base R woul... | What R packages do you find most useful in your daily work? | For me personally, I use the following three packages the most, all available from the awesome Omega Project for Statistical Computing (I do not claim to be an expert, but for my purposes they are ver | What R packages do you find most useful in your daily work?
For me personally, I use the following three packages the most, all available from the awesome Omega Project for Statistical Computing (I do not claim to be an expert, but for my purposes they are very easy to use):
RCurl: It has lots of options which allows ... | What R packages do you find most useful in your daily work?
For me personally, I use the following three packages the most, all available from the awesome Omega Project for Statistical Computing (I do not claim to be an expert, but for my purposes they are ver |
9,703 | What R packages do you find most useful in your daily work? | Sweave lets you embed R code in a LaTeX document. The results of executing the code, and optionally the source code, become part of the final document.
So instead of, for example, pasting an image produced by R into a LaTeX file, you can paste the R code into the file and keep everything in one place. | What R packages do you find most useful in your daily work? | Sweave lets you embed R code in a LaTeX document. The results of executing the code, and optionally the source code, become part of the final document.
So instead of, for example, pasting an image pr | What R packages do you find most useful in your daily work?
Sweave lets you embed R code in a LaTeX document. The results of executing the code, and optionally the source code, become part of the final document.
So instead of, for example, pasting an image produced by R into a LaTeX file, you can paste the R code into... | What R packages do you find most useful in your daily work?
Sweave lets you embed R code in a LaTeX document. The results of executing the code, and optionally the source code, become part of the final document.
So instead of, for example, pasting an image pr |
9,704 | What R packages do you find most useful in your daily work? | I imagine graphics and data manipulation are two things that are useful no matter what you are doing. Thus, I'd recommend:
ggplot2 (great graphics)
lattice (great graphics)
plyr (useful for data manipulation)
Hmisc (good for descriptive statistics and much more) | What R packages do you find most useful in your daily work? | I imagine graphics and data manipulation are two things that are useful no matter what you are doing. Thus, I'd recommend:
ggplot2 (great graphics)
lattice (great graphics)
plyr (useful for data mani | What R packages do you find most useful in your daily work?
I imagine graphics and data manipulation are two things that are useful no matter what you are doing. Thus, I'd recommend:
ggplot2 (great graphics)
lattice (great graphics)
plyr (useful for data manipulation)
Hmisc (good for descriptive statistics and much mo... | What R packages do you find most useful in your daily work?
I imagine graphics and data manipulation are two things that are useful no matter what you are doing. Thus, I'd recommend:
ggplot2 (great graphics)
lattice (great graphics)
plyr (useful for data mani |
9,705 | What R packages do you find most useful in your daily work? | zoo and xts are a must in my work! | What R packages do you find most useful in your daily work? | zoo and xts are a must in my work! | What R packages do you find most useful in your daily work?
zoo and xts are a must in my work! | What R packages do you find most useful in your daily work?
zoo and xts are a must in my work! |
9,706 | What R packages do you find most useful in your daily work? | I find lattice along with the companion book "Lattice: Multivariate Data Visualization with R" by Deepayan Sarkar invaluable. | What R packages do you find most useful in your daily work? | I find lattice along with the companion book "Lattice: Multivariate Data Visualization with R" by Deepayan Sarkar invaluable. | What R packages do you find most useful in your daily work?
I find lattice along with the companion book "Lattice: Multivariate Data Visualization with R" by Deepayan Sarkar invaluable. | What R packages do you find most useful in your daily work?
I find lattice along with the companion book "Lattice: Multivariate Data Visualization with R" by Deepayan Sarkar invaluable. |
9,707 | What R packages do you find most useful in your daily work? | You can get user reviews of packages on crantastic | What R packages do you find most useful in your daily work? | You can get user reviews of packages on crantastic | What R packages do you find most useful in your daily work?
You can get user reviews of packages on crantastic | What R packages do you find most useful in your daily work?
You can get user reviews of packages on crantastic |
9,708 | What R packages do you find most useful in your daily work? | I would suggest using some of the packages provided by revolution R. In particular, I quite like the:
multicore package for parallel computing using shared memory processors
there optimized packages for matrices | What R packages do you find most useful in your daily work? | I would suggest using some of the packages provided by revolution R. In particular, I quite like the:
multicore package for parallel computing using shared memory processors
there optimized packages | What R packages do you find most useful in your daily work?
I would suggest using some of the packages provided by revolution R. In particular, I quite like the:
multicore package for parallel computing using shared memory processors
there optimized packages for matrices | What R packages do you find most useful in your daily work?
I would suggest using some of the packages provided by revolution R. In particular, I quite like the:
multicore package for parallel computing using shared memory processors
there optimized packages |
9,709 | What R packages do you find most useful in your daily work? | If you are doing any kind of predictive modeling, caret is a godsend. Especially combined with the multicore package, some pretty amazing things are possible. | What R packages do you find most useful in your daily work? | If you are doing any kind of predictive modeling, caret is a godsend. Especially combined with the multicore package, some pretty amazing things are possible. | What R packages do you find most useful in your daily work?
If you are doing any kind of predictive modeling, caret is a godsend. Especially combined with the multicore package, some pretty amazing things are possible. | What R packages do you find most useful in your daily work?
If you are doing any kind of predictive modeling, caret is a godsend. Especially combined with the multicore package, some pretty amazing things are possible. |
9,710 | What R packages do you find most useful in your daily work? | Day-to-day the most useful package must be "foreign" which has functions for reading and writing data for other statistical packages e.g. Stata, SPSS, Minitab, SAS, etc. Working in a field where R is not that commonplace means that this is a very important package. | What R packages do you find most useful in your daily work? | Day-to-day the most useful package must be "foreign" which has functions for reading and writing data for other statistical packages e.g. Stata, SPSS, Minitab, SAS, etc. Working in a field where R is | What R packages do you find most useful in your daily work?
Day-to-day the most useful package must be "foreign" which has functions for reading and writing data for other statistical packages e.g. Stata, SPSS, Minitab, SAS, etc. Working in a field where R is not that commonplace means that this is a very important pac... | What R packages do you find most useful in your daily work?
Day-to-day the most useful package must be "foreign" which has functions for reading and writing data for other statistical packages e.g. Stata, SPSS, Minitab, SAS, etc. Working in a field where R is |
9,711 | What R packages do you find most useful in your daily work? | I use
car, doBy, Epi, ggplot2, gregmisc (gdata, gmodels, gplots, gtools), Hmisc, plyr, RCurl, RDCOMClient, reshape, RODBC, TeachingDemos, XML.
a lot. | What R packages do you find most useful in your daily work? | I use
car, doBy, Epi, ggplot2, gregmisc (gdata, gmodels, gplots, gtools), Hmisc, plyr, RCurl, RDCOMClient, reshape, RODBC, TeachingDemos, XML.
a lot. | What R packages do you find most useful in your daily work?
I use
car, doBy, Epi, ggplot2, gregmisc (gdata, gmodels, gplots, gtools), Hmisc, plyr, RCurl, RDCOMClient, reshape, RODBC, TeachingDemos, XML.
a lot. | What R packages do you find most useful in your daily work?
I use
car, doBy, Epi, ggplot2, gregmisc (gdata, gmodels, gplots, gtools), Hmisc, plyr, RCurl, RDCOMClient, reshape, RODBC, TeachingDemos, XML.
a lot. |
9,712 | What R packages do you find most useful in your daily work? | This is definitely a question that doesn't have "an answer". It is completely dependent on what you want to do. That aside, I'll share the packages that I install as a standard with an R update...
install.packages(c("car","gregmisc","xtable","Design","Hmisc","psych",
"CCA", "fda", "zoo", "fiel... | What R packages do you find most useful in your daily work? | This is definitely a question that doesn't have "an answer". It is completely dependent on what you want to do. That aside, I'll share the packages that I install as a standard with an R update...
i | What R packages do you find most useful in your daily work?
This is definitely a question that doesn't have "an answer". It is completely dependent on what you want to do. That aside, I'll share the packages that I install as a standard with an R update...
install.packages(c("car","gregmisc","xtable","Design","Hmisc"... | What R packages do you find most useful in your daily work?
This is definitely a question that doesn't have "an answer". It is completely dependent on what you want to do. That aside, I'll share the packages that I install as a standard with an R update...
i |
9,713 | What R packages do you find most useful in your daily work? | You can also take a look at Task views on CRAN and see if something suit your needs. I agree with @Jeromy for these must-have packages (for data manipulation and plotting). | What R packages do you find most useful in your daily work? | You can also take a look at Task views on CRAN and see if something suit your needs. I agree with @Jeromy for these must-have packages (for data manipulation and plotting). | What R packages do you find most useful in your daily work?
You can also take a look at Task views on CRAN and see if something suit your needs. I agree with @Jeromy for these must-have packages (for data manipulation and plotting). | What R packages do you find most useful in your daily work?
You can also take a look at Task views on CRAN and see if something suit your needs. I agree with @Jeromy for these must-have packages (for data manipulation and plotting). |
9,714 | What R packages do you find most useful in your daily work? | If you are working with Latex, I recommend TikZ Device for outputting nice, Latex-formatted (like PSTricks) graphics. The output you get is text-based Latex code, which can be embedded with include(filename) into any figure environment.
Pros:
Same font in graphics as in your text
Professional look
Cons:
Takes long... | What R packages do you find most useful in your daily work? | If you are working with Latex, I recommend TikZ Device for outputting nice, Latex-formatted (like PSTricks) graphics. The output you get is text-based Latex code, which can be embedded with include(fi | What R packages do you find most useful in your daily work?
If you are working with Latex, I recommend TikZ Device for outputting nice, Latex-formatted (like PSTricks) graphics. The output you get is text-based Latex code, which can be embedded with include(filename) into any figure environment.
Pros:
Same font in g... | What R packages do you find most useful in your daily work?
If you are working with Latex, I recommend TikZ Device for outputting nice, Latex-formatted (like PSTricks) graphics. The output you get is text-based Latex code, which can be embedded with include(fi |
9,715 | What R packages do you find most useful in your daily work? | I use lattice, ggplot2, lubridate, reshape, boot, e1071, car, forecast, and zoo a lot. | What R packages do you find most useful in your daily work? | I use lattice, ggplot2, lubridate, reshape, boot, e1071, car, forecast, and zoo a lot. | What R packages do you find most useful in your daily work?
I use lattice, ggplot2, lubridate, reshape, boot, e1071, car, forecast, and zoo a lot. | What R packages do you find most useful in your daily work?
I use lattice, ggplot2, lubridate, reshape, boot, e1071, car, forecast, and zoo a lot. |
9,716 | What R packages do you find most useful in your daily work? | I could not live without:
lattice for graphics
xlsx or XLConnect for reading Excel files
rtf to create reports in rtf format (I would prefer Sword or R2wd but I cannot install statconn at work; I will surely try odfWeave soon.)
nlme and lme4 for mixed models
ff for working with large arrays | What R packages do you find most useful in your daily work? | I could not live without:
lattice for graphics
xlsx or XLConnect for reading Excel files
rtf to create reports in rtf format (I would prefer Sword or R2wd but I cannot install statconn at work; I wil | What R packages do you find most useful in your daily work?
I could not live without:
lattice for graphics
xlsx or XLConnect for reading Excel files
rtf to create reports in rtf format (I would prefer Sword or R2wd but I cannot install statconn at work; I will surely try odfWeave soon.)
nlme and lme4 for mixed models
... | What R packages do you find most useful in your daily work?
I could not live without:
lattice for graphics
xlsx or XLConnect for reading Excel files
rtf to create reports in rtf format (I would prefer Sword or R2wd but I cannot install statconn at work; I wil |
9,717 | What R packages do you find most useful in your daily work? | I can recommend the new shiny based packages to everyone, it makes data visualisation and inspection interactive and thus easier than writing code in R espacially in the beginning.
A good example would be ggplotgui | What R packages do you find most useful in your daily work? | I can recommend the new shiny based packages to everyone, it makes data visualisation and inspection interactive and thus easier than writing code in R espacially in the beginning.
A good example woul | What R packages do you find most useful in your daily work?
I can recommend the new shiny based packages to everyone, it makes data visualisation and inspection interactive and thus easier than writing code in R espacially in the beginning.
A good example would be ggplotgui | What R packages do you find most useful in your daily work?
I can recommend the new shiny based packages to everyone, it makes data visualisation and inspection interactive and thus easier than writing code in R espacially in the beginning.
A good example woul |
9,718 | What R packages do you find most useful in your daily work? | RODBC for accessing data from databases, sqldf for performing simple SQL queries on dataframes (although I am forcing myself to use native R commands), and ggplot2 and plyr | What R packages do you find most useful in your daily work? | RODBC for accessing data from databases, sqldf for performing simple SQL queries on dataframes (although I am forcing myself to use native R commands), and ggplot2 and plyr | What R packages do you find most useful in your daily work?
RODBC for accessing data from databases, sqldf for performing simple SQL queries on dataframes (although I am forcing myself to use native R commands), and ggplot2 and plyr | What R packages do you find most useful in your daily work?
RODBC for accessing data from databases, sqldf for performing simple SQL queries on dataframes (although I am forcing myself to use native R commands), and ggplot2 and plyr |
9,719 | What R packages do you find most useful in your daily work? | I work with both R and MATLAB and I use R.matlab a lot to transfer data between the two. | What R packages do you find most useful in your daily work? | I work with both R and MATLAB and I use R.matlab a lot to transfer data between the two. | What R packages do you find most useful in your daily work?
I work with both R and MATLAB and I use R.matlab a lot to transfer data between the two. | What R packages do you find most useful in your daily work?
I work with both R and MATLAB and I use R.matlab a lot to transfer data between the two. |
9,720 | What R packages do you find most useful in your daily work? | We mostly use:
ggplot - for charts
stats
e1071 - for SVMs | What R packages do you find most useful in your daily work? | We mostly use:
ggplot - for charts
stats
e1071 - for SVMs | What R packages do you find most useful in your daily work?
We mostly use:
ggplot - for charts
stats
e1071 - for SVMs | What R packages do you find most useful in your daily work?
We mostly use:
ggplot - for charts
stats
e1071 - for SVMs |
9,721 | What R packages do you find most useful in your daily work? | lattice, car, MASS, foreign, party. | What R packages do you find most useful in your daily work? | lattice, car, MASS, foreign, party. | What R packages do you find most useful in your daily work?
lattice, car, MASS, foreign, party. | What R packages do you find most useful in your daily work?
lattice, car, MASS, foreign, party. |
9,722 | What R packages do you find most useful in your daily work? | For me
I am using kernlab for Kernel-based Machine Learning Lab and e1071 for SVM and ggplot2 for graphics | What R packages do you find most useful in your daily work? | For me
I am using kernlab for Kernel-based Machine Learning Lab and e1071 for SVM and ggplot2 for graphics | What R packages do you find most useful in your daily work?
For me
I am using kernlab for Kernel-based Machine Learning Lab and e1071 for SVM and ggplot2 for graphics | What R packages do you find most useful in your daily work?
For me
I am using kernlab for Kernel-based Machine Learning Lab and e1071 for SVM and ggplot2 for graphics |
9,723 | What R packages do you find most useful in your daily work? | I use
ggplot2, vegan and reshape quite often. | What R packages do you find most useful in your daily work? | I use
ggplot2, vegan and reshape quite often. | What R packages do you find most useful in your daily work?
I use
ggplot2, vegan and reshape quite often. | What R packages do you find most useful in your daily work?
I use
ggplot2, vegan and reshape quite often. |
9,724 | What do statisticians do that can't be automated? | @Adam, if you think of statistical researchers analogously to those in other fields - people who build upon the existing methodology and knowledge - then it might make it more clear that the answer to your first question is 'No'.
Statisticians that make a living from simply applying canned software packages could quit... | What do statisticians do that can't be automated? | @Adam, if you think of statistical researchers analogously to those in other fields - people who build upon the existing methodology and knowledge - then it might make it more clear that the answer to | What do statisticians do that can't be automated?
@Adam, if you think of statistical researchers analogously to those in other fields - people who build upon the existing methodology and knowledge - then it might make it more clear that the answer to your first question is 'No'.
Statisticians that make a living from s... | What do statisticians do that can't be automated?
@Adam, if you think of statistical researchers analogously to those in other fields - people who build upon the existing methodology and knowledge - then it might make it more clear that the answer to |
9,725 | What do statisticians do that can't be automated? | Computers will only make statisticians obsolete when strong AI makes humans as a whole obsolete.
The question reminds me of the question about, "If there are all of these robust statistical methods, why do people still use other methods?" Some of the answer is habit and training, but much of it is that the question is ... | What do statisticians do that can't be automated? | Computers will only make statisticians obsolete when strong AI makes humans as a whole obsolete.
The question reminds me of the question about, "If there are all of these robust statistical methods, w | What do statisticians do that can't be automated?
Computers will only make statisticians obsolete when strong AI makes humans as a whole obsolete.
The question reminds me of the question about, "If there are all of these robust statistical methods, why do people still use other methods?" Some of the answer is habit and... | What do statisticians do that can't be automated?
Computers will only make statisticians obsolete when strong AI makes humans as a whole obsolete.
The question reminds me of the question about, "If there are all of these robust statistical methods, w |
9,726 | What do statisticians do that can't be automated? | What can a statistician do that a computer can't? Write the original program they get replaced by.
Beyond that somewhat silly answer, the root of the question is ignoring the actual science of statistics in favor of its mechanics, and entirely discounting the role of the creative process in statistical analysis. This i... | What do statisticians do that can't be automated? | What can a statistician do that a computer can't? Write the original program they get replaced by.
Beyond that somewhat silly answer, the root of the question is ignoring the actual science of statist | What do statisticians do that can't be automated?
What can a statistician do that a computer can't? Write the original program they get replaced by.
Beyond that somewhat silly answer, the root of the question is ignoring the actual science of statistics in favor of its mechanics, and entirely discounting the role of th... | What do statisticians do that can't be automated?
What can a statistician do that a computer can't? Write the original program they get replaced by.
Beyond that somewhat silly answer, the root of the question is ignoring the actual science of statist |
9,727 | What do statisticians do that can't be automated? | Another way to interpret this question might be: "has the rapid increase in automated statistical techniques in recent years corresponded with a decreased demand in jobs for dedicated statisticians and data analysts?"
We can address this question by looking at the data
Data courtesy of indeed.com & revolutions blog | What do statisticians do that can't be automated? | Another way to interpret this question might be: "has the rapid increase in automated statistical techniques in recent years corresponded with a decreased demand in jobs for dedicated statisticians an | What do statisticians do that can't be automated?
Another way to interpret this question might be: "has the rapid increase in automated statistical techniques in recent years corresponded with a decreased demand in jobs for dedicated statisticians and data analysts?"
We can address this question by looking at the data... | What do statisticians do that can't be automated?
Another way to interpret this question might be: "has the rapid increase in automated statistical techniques in recent years corresponded with a decreased demand in jobs for dedicated statisticians an |
9,728 | What do statisticians do that can't be automated? | I don't entirely agree with the premise of the question, i.e. I think there is no way in which computers could ever hope to replace statisticians, but to put a concrete example to why I think that:
The work which statisticians do with scientists, particularly, in the design and interpretation of experiments, requires n... | What do statisticians do that can't be automated? | I don't entirely agree with the premise of the question, i.e. I think there is no way in which computers could ever hope to replace statisticians, but to put a concrete example to why I think that:
Th | What do statisticians do that can't be automated?
I don't entirely agree with the premise of the question, i.e. I think there is no way in which computers could ever hope to replace statisticians, but to put a concrete example to why I think that:
The work which statisticians do with scientists, particularly, in the de... | What do statisticians do that can't be automated?
I don't entirely agree with the premise of the question, i.e. I think there is no way in which computers could ever hope to replace statisticians, but to put a concrete example to why I think that:
Th |
9,729 | What do statisticians do that can't be automated? | The question suggests a naive view of a statistician-—that it's all about checking to see if a p < 0.05 and reporting some numbers and standard graphs. If that's what you mean by statistician then you are correct in your implication that much of it could be entirely automated. But that's not what statistician means.
... | What do statisticians do that can't be automated? | The question suggests a naive view of a statistician-—that it's all about checking to see if a p < 0.05 and reporting some numbers and standard graphs. If that's what you mean by statistician then yo | What do statisticians do that can't be automated?
The question suggests a naive view of a statistician-—that it's all about checking to see if a p < 0.05 and reporting some numbers and standard graphs. If that's what you mean by statistician then you are correct in your implication that much of it could be entirely au... | What do statisticians do that can't be automated?
The question suggests a naive view of a statistician-—that it's all about checking to see if a p < 0.05 and reporting some numbers and standard graphs. If that's what you mean by statistician then yo |
9,730 | What do statisticians do that can't be automated? | Loading a statistics package onto your computer doesn't make you a statistician any more than buying a car makes you able to drive.
Even if the statistician just applies "canned" routines there are lots of questions.
Which routine? What routine will answer the client's questions?
With what variables? and should they ... | What do statisticians do that can't be automated? | Loading a statistics package onto your computer doesn't make you a statistician any more than buying a car makes you able to drive.
Even if the statistician just applies "canned" routines there are lo | What do statisticians do that can't be automated?
Loading a statistics package onto your computer doesn't make you a statistician any more than buying a car makes you able to drive.
Even if the statistician just applies "canned" routines there are lots of questions.
Which routine? What routine will answer the client'... | What do statisticians do that can't be automated?
Loading a statistics package onto your computer doesn't make you a statistician any more than buying a car makes you able to drive.
Even if the statistician just applies "canned" routines there are lo |
9,731 | What do statisticians do that can't be automated? | Academic studies which look at the probability of automation of different occupations or task do not think that statisticians will be soon substituted by computers. See for example the controversial Frey & Osborne (2013) study which ranks occupations according to their probability of computerization, statisticians are ... | What do statisticians do that can't be automated? | Academic studies which look at the probability of automation of different occupations or task do not think that statisticians will be soon substituted by computers. See for example the controversial F | What do statisticians do that can't be automated?
Academic studies which look at the probability of automation of different occupations or task do not think that statisticians will be soon substituted by computers. See for example the controversial Frey & Osborne (2013) study which ranks occupations according to their ... | What do statisticians do that can't be automated?
Academic studies which look at the probability of automation of different occupations or task do not think that statisticians will be soon substituted by computers. See for example the controversial F |
9,732 | What do statisticians do that can't be automated? | I think that AI will only make statisticians smarter and more competitive. Why? Because this is the intent of artificial intelligence since their conception many decades ago... | What do statisticians do that can't be automated? | I think that AI will only make statisticians smarter and more competitive. Why? Because this is the intent of artificial intelligence since their conception many decades ago... | What do statisticians do that can't be automated?
I think that AI will only make statisticians smarter and more competitive. Why? Because this is the intent of artificial intelligence since their conception many decades ago... | What do statisticians do that can't be automated?
I think that AI will only make statisticians smarter and more competitive. Why? Because this is the intent of artificial intelligence since their conception many decades ago... |
9,733 | Understanding t-test for linear regression | You're probably thinking of the two sample $t$ test because that's often the first place the $t$ distribution comes up. But really all a $t$ test means is that the reference distribution for the test statistic is a $t$ distribution. If $Z \sim \mathcal N(0,1)$ and $S^2 \sim \chi^2_d$ with $Z$ and $S^2$ independent, the... | Understanding t-test for linear regression | You're probably thinking of the two sample $t$ test because that's often the first place the $t$ distribution comes up. But really all a $t$ test means is that the reference distribution for the test | Understanding t-test for linear regression
You're probably thinking of the two sample $t$ test because that's often the first place the $t$ distribution comes up. But really all a $t$ test means is that the reference distribution for the test statistic is a $t$ distribution. If $Z \sim \mathcal N(0,1)$ and $S^2 \sim \c... | Understanding t-test for linear regression
You're probably thinking of the two sample $t$ test because that's often the first place the $t$ distribution comes up. But really all a $t$ test means is that the reference distribution for the test |
9,734 | Understanding t-test for linear regression | @Chaconne's answer is great. But here is a much shorter nonmathematical version!
Since the goal is to compute a P value, you first need to define a null hypothesis. Almost always, that is that the slope is actually horizontal so the numerical value for the slope (beta) is 0.0.
The slope fit from your data is not 0.0. I... | Understanding t-test for linear regression | @Chaconne's answer is great. But here is a much shorter nonmathematical version!
Since the goal is to compute a P value, you first need to define a null hypothesis. Almost always, that is that the slo | Understanding t-test for linear regression
@Chaconne's answer is great. But here is a much shorter nonmathematical version!
Since the goal is to compute a P value, you first need to define a null hypothesis. Almost always, that is that the slope is actually horizontal so the numerical value for the slope (beta) is 0.0.... | Understanding t-test for linear regression
@Chaconne's answer is great. But here is a much shorter nonmathematical version!
Since the goal is to compute a P value, you first need to define a null hypothesis. Almost always, that is that the slo |
9,735 | Understanding t-test for linear regression | The coefficient estimates the effect of the corresponding IV on the DV; the standard error of that coefficient estimates the average error in that coefficient's estimates; the t-test tells you how many times larger the coefficient itself is than the average error of the values it estimates.
If y'=30x, but the observed ... | Understanding t-test for linear regression | The coefficient estimates the effect of the corresponding IV on the DV; the standard error of that coefficient estimates the average error in that coefficient's estimates; the t-test tells you how man | Understanding t-test for linear regression
The coefficient estimates the effect of the corresponding IV on the DV; the standard error of that coefficient estimates the average error in that coefficient's estimates; the t-test tells you how many times larger the coefficient itself is than the average error of the values... | Understanding t-test for linear regression
The coefficient estimates the effect of the corresponding IV on the DV; the standard error of that coefficient estimates the average error in that coefficient's estimates; the t-test tells you how man |
9,736 | Do we need hypothesis testing when we have all the population? | To illustrate my points, I will assume that everybody has been asked whether they prefer Star Trek or Doctor Who and has to choose one of them (there is no neutral option).
To keep things simple, let’s also assume that your census data is actually complete and accurate (which it rarely ever is).
There are some importan... | Do we need hypothesis testing when we have all the population? | To illustrate my points, I will assume that everybody has been asked whether they prefer Star Trek or Doctor Who and has to choose one of them (there is no neutral option).
To keep things simple, let’ | Do we need hypothesis testing when we have all the population?
To illustrate my points, I will assume that everybody has been asked whether they prefer Star Trek or Doctor Who and has to choose one of them (there is no neutral option).
To keep things simple, let’s also assume that your census data is actually complete ... | Do we need hypothesis testing when we have all the population?
To illustrate my points, I will assume that everybody has been asked whether they prefer Star Trek or Doctor Who and has to choose one of them (there is no neutral option).
To keep things simple, let’ |
9,737 | Do we need hypothesis testing when we have all the population? | It all depends on your goal.
If you want to know how many people smoke and how many people die of lung cancer you can just count them, but if you want to know whether smoking increases the risk for lung cancer then you need statistical inference.
If you want to know high school students' educational attainments, you ca... | Do we need hypothesis testing when we have all the population? | It all depends on your goal.
If you want to know how many people smoke and how many people die of lung cancer you can just count them, but if you want to know whether smoking increases the risk for lu | Do we need hypothesis testing when we have all the population?
It all depends on your goal.
If you want to know how many people smoke and how many people die of lung cancer you can just count them, but if you want to know whether smoking increases the risk for lung cancer then you need statistical inference.
If you wan... | Do we need hypothesis testing when we have all the population?
It all depends on your goal.
If you want to know how many people smoke and how many people die of lung cancer you can just count them, but if you want to know whether smoking increases the risk for lu |
9,738 | Do we need hypothesis testing when we have all the population? | Funny. I spent years explaining to clients that in cases with true census information there was no variance and therefore statistical significance was meaningless.
Example: If I have data from 150 stores in a supermarket chain that says 15000 cases of Coke and 16000 cases of Pepsi were sold in a week, we can definitely... | Do we need hypothesis testing when we have all the population? | Funny. I spent years explaining to clients that in cases with true census information there was no variance and therefore statistical significance was meaningless.
Example: If I have data from 150 sto | Do we need hypothesis testing when we have all the population?
Funny. I spent years explaining to clients that in cases with true census information there was no variance and therefore statistical significance was meaningless.
Example: If I have data from 150 stores in a supermarket chain that says 15000 cases of Coke ... | Do we need hypothesis testing when we have all the population?
Funny. I spent years explaining to clients that in cases with true census information there was no variance and therefore statistical significance was meaningless.
Example: If I have data from 150 sto |
9,739 | Do we need hypothesis testing when we have all the population? | In typical applications of hypothesis testing, you do not have access to the whole population of interest, but you want to make statements about the parameters that govern the distribution of the data in the population (mean, variance, correlation,...). Then, you take a sample from the population, and assess if the sam... | Do we need hypothesis testing when we have all the population? | In typical applications of hypothesis testing, you do not have access to the whole population of interest, but you want to make statements about the parameters that govern the distribution of the data | Do we need hypothesis testing when we have all the population?
In typical applications of hypothesis testing, you do not have access to the whole population of interest, but you want to make statements about the parameters that govern the distribution of the data in the population (mean, variance, correlation,...). The... | Do we need hypothesis testing when we have all the population?
In typical applications of hypothesis testing, you do not have access to the whole population of interest, but you want to make statements about the parameters that govern the distribution of the data |
9,740 | Do we need hypothesis testing when we have all the population? | Let's say you are measuring height in the current world population and you want to caompare male and female height.
To check the hypothesis "average male height for men alive today is higher than for women alive today", you can just measure every man and woman on the planet and compare the results. If male height is on... | Do we need hypothesis testing when we have all the population? | Let's say you are measuring height in the current world population and you want to caompare male and female height.
To check the hypothesis "average male height for men alive today is higher than for | Do we need hypothesis testing when we have all the population?
Let's say you are measuring height in the current world population and you want to caompare male and female height.
To check the hypothesis "average male height for men alive today is higher than for women alive today", you can just measure every man and wo... | Do we need hypothesis testing when we have all the population?
Let's say you are measuring height in the current world population and you want to caompare male and female height.
To check the hypothesis "average male height for men alive today is higher than for |
9,741 | Do we need hypothesis testing when we have all the population? | I would be very wary about anyone claiming to have knowledge about the complete population. There is a lot of confusion about what this term means in a statistical context, leading to people claiming they have the complete population, when they actually don't. And where the complete population is known, the scientific ... | Do we need hypothesis testing when we have all the population? | I would be very wary about anyone claiming to have knowledge about the complete population. There is a lot of confusion about what this term means in a statistical context, leading to people claiming | Do we need hypothesis testing when we have all the population?
I would be very wary about anyone claiming to have knowledge about the complete population. There is a lot of confusion about what this term means in a statistical context, leading to people claiming they have the complete population, when they actually don... | Do we need hypothesis testing when we have all the population?
I would be very wary about anyone claiming to have knowledge about the complete population. There is a lot of confusion about what this term means in a statistical context, leading to people claiming |
9,742 | Do we need hypothesis testing when we have all the population? | Let me add something at the good answers above. Some of them address mainly the problem of reliability of the condition “have all the population”, as the accepted one, and related practical points.
I propose a more theoretical perspective, related to the Sergio’s answer but not equal.
If you say you “have all the popul... | Do we need hypothesis testing when we have all the population? | Let me add something at the good answers above. Some of them address mainly the problem of reliability of the condition “have all the population”, as the accepted one, and related practical points.
I | Do we need hypothesis testing when we have all the population?
Let me add something at the good answers above. Some of them address mainly the problem of reliability of the condition “have all the population”, as the accepted one, and related practical points.
I propose a more theoretical perspective, related to the Se... | Do we need hypothesis testing when we have all the population?
Let me add something at the good answers above. Some of them address mainly the problem of reliability of the condition “have all the population”, as the accepted one, and related practical points.
I |
9,743 | Real life examples of distributions with negative skewness | In the UK, price of a book. There is a "Recommended retail price" which will generally be the modal price, and virtually nowhere would you have to pay more. But some shops will discount, and a few will discount heavily.
Also, age at retirement. Most people retire at 65-68 which is when the state pension kicks in, very ... | Real life examples of distributions with negative skewness | In the UK, price of a book. There is a "Recommended retail price" which will generally be the modal price, and virtually nowhere would you have to pay more. But some shops will discount, and a few wil | Real life examples of distributions with negative skewness
In the UK, price of a book. There is a "Recommended retail price" which will generally be the modal price, and virtually nowhere would you have to pay more. But some shops will discount, and a few will discount heavily.
Also, age at retirement. Most people reti... | Real life examples of distributions with negative skewness
In the UK, price of a book. There is a "Recommended retail price" which will generally be the modal price, and virtually nowhere would you have to pay more. But some shops will discount, and a few wil |
9,744 | Real life examples of distributions with negative skewness | Nick Cox accurately commented that "age at death is negatively skewed in developed countries" which I thought was a great example.
I found the most convenient figures I could lay my hands on came from the Australian Bureau of Statistics (in particular, I used this Excel sheet), since their age bins went up to 100 year ... | Real life examples of distributions with negative skewness | Nick Cox accurately commented that "age at death is negatively skewed in developed countries" which I thought was a great example.
I found the most convenient figures I could lay my hands on came from | Real life examples of distributions with negative skewness
Nick Cox accurately commented that "age at death is negatively skewed in developed countries" which I thought was a great example.
I found the most convenient figures I could lay my hands on came from the Australian Bureau of Statistics (in particular, I used t... | Real life examples of distributions with negative skewness
Nick Cox accurately commented that "age at death is negatively skewed in developed countries" which I thought was a great example.
I found the most convenient figures I could lay my hands on came from |
9,745 | Real life examples of distributions with negative skewness | Here are the results for the forty athletes who successfully completed a legal jump in the qualifying round of the 2012 Olympic men's long jump, presented in a kernel density plot with rug plot underneath.
It seems to be much easier to be a metre behind the main group of competitors than to be a metre ahead, which wou... | Real life examples of distributions with negative skewness | Here are the results for the forty athletes who successfully completed a legal jump in the qualifying round of the 2012 Olympic men's long jump, presented in a kernel density plot with rug plot undern | Real life examples of distributions with negative skewness
Here are the results for the forty athletes who successfully completed a legal jump in the qualifying round of the 2012 Olympic men's long jump, presented in a kernel density plot with rug plot underneath.
It seems to be much easier to be a metre behind the ma... | Real life examples of distributions with negative skewness
Here are the results for the forty athletes who successfully completed a legal jump in the qualifying round of the 2012 Olympic men's long jump, presented in a kernel density plot with rug plot undern |
9,746 | Real life examples of distributions with negative skewness | Scores on easy tests, or alternatively, scores on tests for which students are especially motivated, tend to be left skew.
As a result, the SAT/ACT scores of students entering sought after colleges (and even more so, their GPAs) tend to be left skew. There's plenty of examples at collegeapps.about.com e.g. a plot of Un... | Real life examples of distributions with negative skewness | Scores on easy tests, or alternatively, scores on tests for which students are especially motivated, tend to be left skew.
As a result, the SAT/ACT scores of students entering sought after colleges (a | Real life examples of distributions with negative skewness
Scores on easy tests, or alternatively, scores on tests for which students are especially motivated, tend to be left skew.
As a result, the SAT/ACT scores of students entering sought after colleges (and even more so, their GPAs) tend to be left skew. There's pl... | Real life examples of distributions with negative skewness
Scores on easy tests, or alternatively, scores on tests for which students are especially motivated, tend to be left skew.
As a result, the SAT/ACT scores of students entering sought after colleges (a |
9,747 | Real life examples of distributions with negative skewness | In Stochastic Frontier Analysis, and specifically in its historically initial focus, production, the production function of a firm/production unit in general, is specified stochastically as
$$q = f(\mathbf x) + u-w$$
where $q$ is the actual output produced by the firm, and $f(\mathbf x)$ is its production function (whi... | Real life examples of distributions with negative skewness | In Stochastic Frontier Analysis, and specifically in its historically initial focus, production, the production function of a firm/production unit in general, is specified stochastically as
$$q = f(\m | Real life examples of distributions with negative skewness
In Stochastic Frontier Analysis, and specifically in its historically initial focus, production, the production function of a firm/production unit in general, is specified stochastically as
$$q = f(\mathbf x) + u-w$$
where $q$ is the actual output produced by t... | Real life examples of distributions with negative skewness
In Stochastic Frontier Analysis, and specifically in its historically initial focus, production, the production function of a firm/production unit in general, is specified stochastically as
$$q = f(\m |
9,748 | Real life examples of distributions with negative skewness | Asset price changes (returns) typically have negative skew - many small price increases with a few large price drops. The skew seems to hold for almost all types of assets: stocks prices, commodity prices, etc. The negative skew can be observed in monthly price changes but is much more evident when you start looking at... | Real life examples of distributions with negative skewness | Asset price changes (returns) typically have negative skew - many small price increases with a few large price drops. The skew seems to hold for almost all types of assets: stocks prices, commodity pr | Real life examples of distributions with negative skewness
Asset price changes (returns) typically have negative skew - many small price increases with a few large price drops. The skew seems to hold for almost all types of assets: stocks prices, commodity prices, etc. The negative skew can be observed in monthly price... | Real life examples of distributions with negative skewness
Asset price changes (returns) typically have negative skew - many small price increases with a few large price drops. The skew seems to hold for almost all types of assets: stocks prices, commodity pr |
9,749 | Real life examples of distributions with negative skewness | Negative skewness is common in flood hydrology. Below is an example of a flood frequency curve (South Creek at Mulgoa Rd, lat -33.8783, lon 150.7683) which I've taken from 'Australian Rainfall and Runoff' (ARR) the guide to flood estimation developed by Engineers, Australia.
There is a comment in ARR:
With negative s... | Real life examples of distributions with negative skewness | Negative skewness is common in flood hydrology. Below is an example of a flood frequency curve (South Creek at Mulgoa Rd, lat -33.8783, lon 150.7683) which I've taken from 'Australian Rainfall and Ru | Real life examples of distributions with negative skewness
Negative skewness is common in flood hydrology. Below is an example of a flood frequency curve (South Creek at Mulgoa Rd, lat -33.8783, lon 150.7683) which I've taken from 'Australian Rainfall and Runoff' (ARR) the guide to flood estimation developed by Engine... | Real life examples of distributions with negative skewness
Negative skewness is common in flood hydrology. Below is an example of a flood frequency curve (South Creek at Mulgoa Rd, lat -33.8783, lon 150.7683) which I've taken from 'Australian Rainfall and Ru |
9,750 | Real life examples of distributions with negative skewness | Gestational age at delivery (especially for live births) is left skewed. Infants can be born alive very early (although chances of continued survival are small when too early), peak between 36-41 weeks, and drop fast. It is typical for women in the US to be induced if 41/42 weeks, so we don't usually see many deliverie... | Real life examples of distributions with negative skewness | Gestational age at delivery (especially for live births) is left skewed. Infants can be born alive very early (although chances of continued survival are small when too early), peak between 36-41 week | Real life examples of distributions with negative skewness
Gestational age at delivery (especially for live births) is left skewed. Infants can be born alive very early (although chances of continued survival are small when too early), peak between 36-41 weeks, and drop fast. It is typical for women in the US to be ind... | Real life examples of distributions with negative skewness
Gestational age at delivery (especially for live births) is left skewed. Infants can be born alive very early (although chances of continued survival are small when too early), peak between 36-41 week |
9,751 | Real life examples of distributions with negative skewness | In fisheries there are often examples of negative skew because of regulatory requirements. For instance the length distribution of fish released in recreational fishery; because there is sometimes a minimum length that a fish must be in order for it to be retained all fish under the limit are discarded. But because peo... | Real life examples of distributions with negative skewness | In fisheries there are often examples of negative skew because of regulatory requirements. For instance the length distribution of fish released in recreational fishery; because there is sometimes a m | Real life examples of distributions with negative skewness
In fisheries there are often examples of negative skew because of regulatory requirements. For instance the length distribution of fish released in recreational fishery; because there is sometimes a minimum length that a fish must be in order for it to be retai... | Real life examples of distributions with negative skewness
In fisheries there are often examples of negative skew because of regulatory requirements. For instance the length distribution of fish released in recreational fishery; because there is sometimes a m |
9,752 | Real life examples of distributions with negative skewness | Some great suggestions have been made on this thread. On the theme of age-related mortality, machine failure rates are frequently a function of machine age and would fall into this class of distributions. In addition to the financial factors already noted, financial loss functions and distributions typically resemble t... | Real life examples of distributions with negative skewness | Some great suggestions have been made on this thread. On the theme of age-related mortality, machine failure rates are frequently a function of machine age and would fall into this class of distributi | Real life examples of distributions with negative skewness
Some great suggestions have been made on this thread. On the theme of age-related mortality, machine failure rates are frequently a function of machine age and would fall into this class of distributions. In addition to the financial factors already noted, fina... | Real life examples of distributions with negative skewness
Some great suggestions have been made on this thread. On the theme of age-related mortality, machine failure rates are frequently a function of machine age and would fall into this class of distributi |
9,753 | Real life examples of distributions with negative skewness | Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
Age of retirement in the U.S. is negatively skewed. Th... | Real life examples of distributions with negative skewness | Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
| Real life examples of distributions with negative skewness
Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
... | Real life examples of distributions with negative skewness
Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
|
9,754 | Real life examples of distributions with negative skewness | In random matrix theory, the Tracy Widom distribution is right-skewed. This is the distribution of the largest eigenvalue of a random matrix. By symmetry, the smallest eigenvalue has negative Tracy Widom distribution, and is therefore left-skewed.
This is roughly due to the fact that random eigenvalues are akin to cha... | Real life examples of distributions with negative skewness | In random matrix theory, the Tracy Widom distribution is right-skewed. This is the distribution of the largest eigenvalue of a random matrix. By symmetry, the smallest eigenvalue has negative Tracy Wi | Real life examples of distributions with negative skewness
In random matrix theory, the Tracy Widom distribution is right-skewed. This is the distribution of the largest eigenvalue of a random matrix. By symmetry, the smallest eigenvalue has negative Tracy Widom distribution, and is therefore left-skewed.
This is roug... | Real life examples of distributions with negative skewness
In random matrix theory, the Tracy Widom distribution is right-skewed. This is the distribution of the largest eigenvalue of a random matrix. By symmetry, the smallest eigenvalue has negative Tracy Wi |
9,755 | How to add non-linear trend line to a scatter plot in R? [closed] | Let's create some data.
n <- 100
x <- seq(n)
y <- rnorm(n, 50 + 30 * x^(-0.2), 1)
Data <- data.frame(x, y)
The following shows how you can fit a loess line or the fit of a non-linear regression.
plot(y ~ x, Data)
# fit a loess line
loess_fit <- loess(y ~ x, Data)
lines(Data$x, predict(loess_fit), col = "blue")
# fit... | How to add non-linear trend line to a scatter plot in R? [closed] | Let's create some data.
n <- 100
x <- seq(n)
y <- rnorm(n, 50 + 30 * x^(-0.2), 1)
Data <- data.frame(x, y)
The following shows how you can fit a loess line or the fit of a non-linear regression.
plot | How to add non-linear trend line to a scatter plot in R? [closed]
Let's create some data.
n <- 100
x <- seq(n)
y <- rnorm(n, 50 + 30 * x^(-0.2), 1)
Data <- data.frame(x, y)
The following shows how you can fit a loess line or the fit of a non-linear regression.
plot(y ~ x, Data)
# fit a loess line
loess_fit <- loess(y... | How to add non-linear trend line to a scatter plot in R? [closed]
Let's create some data.
n <- 100
x <- seq(n)
y <- rnorm(n, 50 + 30 * x^(-0.2), 1)
Data <- data.frame(x, y)
The following shows how you can fit a loess line or the fit of a non-linear regression.
plot |
9,756 | How to add non-linear trend line to a scatter plot in R? [closed] | If you use ggplot2 (the third plotting system, in R, after base R and lattice), this becomes:
library(ggplot2)
ggplot(Data, aes(x,y)) + geom_point() + geom_smooth()
You can choose how the data is smoothed: see ?stat_smooth for details and examples. | How to add non-linear trend line to a scatter plot in R? [closed] | If you use ggplot2 (the third plotting system, in R, after base R and lattice), this becomes:
library(ggplot2)
ggplot(Data, aes(x,y)) + geom_point() + geom_smooth()
You can choose how the data is sm | How to add non-linear trend line to a scatter plot in R? [closed]
If you use ggplot2 (the third plotting system, in R, after base R and lattice), this becomes:
library(ggplot2)
ggplot(Data, aes(x,y)) + geom_point() + geom_smooth()
You can choose how the data is smoothed: see ?stat_smooth for details and examples. | How to add non-linear trend line to a scatter plot in R? [closed]
If you use ggplot2 (the third plotting system, in R, after base R and lattice), this becomes:
library(ggplot2)
ggplot(Data, aes(x,y)) + geom_point() + geom_smooth()
You can choose how the data is sm |
9,757 | How to add non-linear trend line to a scatter plot in R? [closed] | Without knowing exactly what you are looking for, using the lattice package you can easily add a loess curve with type="smooth"; e.g.,
> library(lattice)
> x <- rnorm(100)
> y <- rnorm(100)
> xyplot(y ~ x, type=c("smooth", "p"))
See help("panel.loess") for arguments that can be passed to the loess fitting routine in o... | How to add non-linear trend line to a scatter plot in R? [closed] | Without knowing exactly what you are looking for, using the lattice package you can easily add a loess curve with type="smooth"; e.g.,
> library(lattice)
> x <- rnorm(100)
> y <- rnorm(100)
> xyplot(y | How to add non-linear trend line to a scatter plot in R? [closed]
Without knowing exactly what you are looking for, using the lattice package you can easily add a loess curve with type="smooth"; e.g.,
> library(lattice)
> x <- rnorm(100)
> y <- rnorm(100)
> xyplot(y ~ x, type=c("smooth", "p"))
See help("panel.loess") ... | How to add non-linear trend line to a scatter plot in R? [closed]
Without knowing exactly what you are looking for, using the lattice package you can easily add a loess curve with type="smooth"; e.g.,
> library(lattice)
> x <- rnorm(100)
> y <- rnorm(100)
> xyplot(y |
9,758 | How to add non-linear trend line to a scatter plot in R? [closed] | Your question is a bit vague, so I'm going to make some assumptions about what your problem is. It would help a lot if you could put up a scatterplot and describe the data a bit. Please, if I'm making bad assumptions then ignore my answer.
First, it's possible that your data describe some process which you reasonably b... | How to add non-linear trend line to a scatter plot in R? [closed] | Your question is a bit vague, so I'm going to make some assumptions about what your problem is. It would help a lot if you could put up a scatterplot and describe the data a bit. Please, if I'm making | How to add non-linear trend line to a scatter plot in R? [closed]
Your question is a bit vague, so I'm going to make some assumptions about what your problem is. It would help a lot if you could put up a scatterplot and describe the data a bit. Please, if I'm making bad assumptions then ignore my answer.
First, it's po... | How to add non-linear trend line to a scatter plot in R? [closed]
Your question is a bit vague, so I'm going to make some assumptions about what your problem is. It would help a lot if you could put up a scatterplot and describe the data a bit. Please, if I'm making |
9,759 | How to add non-linear trend line to a scatter plot in R? [closed] | Putting scatter plot sample points and smooth curve on same graph:
library(graphics)
## Create some x,y sample points falling on hyperbola, but with error:
xSample = seq(0.1, 1.0, 0.1)
ySample = 1.0 / xSample
numPts <- length(xSample)
ySample <- ySample + 0.5 * rnorm(numPts) ## Add some noise
## Create x... | How to add non-linear trend line to a scatter plot in R? [closed] | Putting scatter plot sample points and smooth curve on same graph:
library(graphics)
## Create some x,y sample points falling on hyperbola, but with error:
xSample = seq(0.1, 1.0, 0.1)
ySample | How to add non-linear trend line to a scatter plot in R? [closed]
Putting scatter plot sample points and smooth curve on same graph:
library(graphics)
## Create some x,y sample points falling on hyperbola, but with error:
xSample = seq(0.1, 1.0, 0.1)
ySample = 1.0 / xSample
numPts <- length(xSample)
ySample... | How to add non-linear trend line to a scatter plot in R? [closed]
Putting scatter plot sample points and smooth curve on same graph:
library(graphics)
## Create some x,y sample points falling on hyperbola, but with error:
xSample = seq(0.1, 1.0, 0.1)
ySample |
9,760 | Expectation of reciprocal of a variable | can it be 1/E(X)?
No, in general it can't; Jensen's inequality tells us that if $X$ is a random variable and $\varphi$ is a convex function, then $\varphi(\text{E}[X]) \leq \text{E}\left[\varphi(X)\right]$. If $X$ is strictly positive, then $1/X$ is convex, so $\text{E}[1/X]\geq 1/\text{E}[X]$, and for a strictly conv... | Expectation of reciprocal of a variable | can it be 1/E(X)?
No, in general it can't; Jensen's inequality tells us that if $X$ is a random variable and $\varphi$ is a convex function, then $\varphi(\text{E}[X]) \leq \text{E}\left[\varphi(X)\r | Expectation of reciprocal of a variable
can it be 1/E(X)?
No, in general it can't; Jensen's inequality tells us that if $X$ is a random variable and $\varphi$ is a convex function, then $\varphi(\text{E}[X]) \leq \text{E}\left[\varphi(X)\right]$. If $X$ is strictly positive, then $1/X$ is convex, so $\text{E}[1/X]\geq... | Expectation of reciprocal of a variable
can it be 1/E(X)?
No, in general it can't; Jensen's inequality tells us that if $X$ is a random variable and $\varphi$ is a convex function, then $\varphi(\text{E}[X]) \leq \text{E}\left[\varphi(X)\r |
9,761 | Expectation of reciprocal of a variable | As Glen_b says that's probably wrong, because the reciprocal is a non-linear function. If you want an approximation to $E(1/X)$ maybe you can use a Taylor expansion around $E(X)$:
$$
E \bigg( \frac{1}{X} \bigg) \approx E\bigg( \frac{1}{E(X)} - \frac{1}{E(X)^2}(X-E(X)) + \frac{1}{E(X)^3}(X - E(X))^2 \bigg) = \\
= \fra... | Expectation of reciprocal of a variable | As Glen_b says that's probably wrong, because the reciprocal is a non-linear function. If you want an approximation to $E(1/X)$ maybe you can use a Taylor expansion around $E(X)$:
$$
E \bigg( \frac{1} | Expectation of reciprocal of a variable
As Glen_b says that's probably wrong, because the reciprocal is a non-linear function. If you want an approximation to $E(1/X)$ maybe you can use a Taylor expansion around $E(X)$:
$$
E \bigg( \frac{1}{X} \bigg) \approx E\bigg( \frac{1}{E(X)} - \frac{1}{E(X)^2}(X-E(X)) + \frac{1}{... | Expectation of reciprocal of a variable
As Glen_b says that's probably wrong, because the reciprocal is a non-linear function. If you want an approximation to $E(1/X)$ maybe you can use a Taylor expansion around $E(X)$:
$$
E \bigg( \frac{1} |
9,762 | Expectation of reciprocal of a variable | Others have already explained that the answer to the question is NO, except trivial cases. Below we give an approach to finding $\DeclareMathOperator{\E}{\mathbb{E}} \E \frac1{X}$ when $X>0$ with probability one, and the moment generating function $M_X(t) = \E e^{tX}$ do exist. An application of this method (and a ge... | Expectation of reciprocal of a variable | Others have already explained that the answer to the question is NO, except trivial cases. Below we give an approach to finding $\DeclareMathOperator{\E}{\mathbb{E}} \E \frac1{X}$ when $X>0$ with pro | Expectation of reciprocal of a variable
Others have already explained that the answer to the question is NO, except trivial cases. Below we give an approach to finding $\DeclareMathOperator{\E}{\mathbb{E}} \E \frac1{X}$ when $X>0$ with probability one, and the moment generating function $M_X(t) = \E e^{tX}$ do exist. ... | Expectation of reciprocal of a variable
Others have already explained that the answer to the question is NO, except trivial cases. Below we give an approach to finding $\DeclareMathOperator{\E}{\mathbb{E}} \E \frac1{X}$ when $X>0$ with pro |
9,763 | Expectation of reciprocal of a variable | An alternative approach to calculating $E(1/X)$ knowing X is a positive random variable is through its moment generating function $E[e^{-\lambda X}]$.
Since by elementary calculas
$$
\int_0^\infty e^{-\lambda x} d\lambda =\frac{1}{x}
$$
we have, by Fubini's theorem
$$
\int_0^\infty E[e^{-\lambda X}] d\lambda =E[\fra... | Expectation of reciprocal of a variable | An alternative approach to calculating $E(1/X)$ knowing X is a positive random variable is through its moment generating function $E[e^{-\lambda X}]$.
Since by elementary calculas
$$
\int_0^\infty | Expectation of reciprocal of a variable
An alternative approach to calculating $E(1/X)$ knowing X is a positive random variable is through its moment generating function $E[e^{-\lambda X}]$.
Since by elementary calculas
$$
\int_0^\infty e^{-\lambda x} d\lambda =\frac{1}{x}
$$
we have, by Fubini's theorem
$$
\int_0^\... | Expectation of reciprocal of a variable
An alternative approach to calculating $E(1/X)$ knowing X is a positive random variable is through its moment generating function $E[e^{-\lambda X}]$.
Since by elementary calculas
$$
\int_0^\infty |
9,764 | Expectation of reciprocal of a variable | To first give an intuition, what about using the discrete case in finite sample to illustrate that $\text{E}(1/X)\neq 1/\text{E}(X)$ (putting aside cases such as $\text{E}(X)=0$)?
In finite sample, using the term average for expectation is not that abusive, thus if one has on the one hand
$\text{E}(X) = \frac{1}{N}\sum... | Expectation of reciprocal of a variable | To first give an intuition, what about using the discrete case in finite sample to illustrate that $\text{E}(1/X)\neq 1/\text{E}(X)$ (putting aside cases such as $\text{E}(X)=0$)?
In finite sample, us | Expectation of reciprocal of a variable
To first give an intuition, what about using the discrete case in finite sample to illustrate that $\text{E}(1/X)\neq 1/\text{E}(X)$ (putting aside cases such as $\text{E}(X)=0$)?
In finite sample, using the term average for expectation is not that abusive, thus if one has on the... | Expectation of reciprocal of a variable
To first give an intuition, what about using the discrete case in finite sample to illustrate that $\text{E}(1/X)\neq 1/\text{E}(X)$ (putting aside cases such as $\text{E}(X)=0$)?
In finite sample, us |
9,765 | What is the difference between convolutional neural networks and deep learning? | Deep Learning is the branch of Machine Learning based on Deep Neural Networks (DNNs), meaning neural networks with at the very least 3 or 4 layers (including the input and output layers). But for some people (especially non-technical), any neural net qualifies as Deep Learning, regardless of its depth. And others consi... | What is the difference between convolutional neural networks and deep learning? | Deep Learning is the branch of Machine Learning based on Deep Neural Networks (DNNs), meaning neural networks with at the very least 3 or 4 layers (including the input and output layers). But for some | What is the difference between convolutional neural networks and deep learning?
Deep Learning is the branch of Machine Learning based on Deep Neural Networks (DNNs), meaning neural networks with at the very least 3 or 4 layers (including the input and output layers). But for some people (especially non-technical), any ... | What is the difference between convolutional neural networks and deep learning?
Deep Learning is the branch of Machine Learning based on Deep Neural Networks (DNNs), meaning neural networks with at the very least 3 or 4 layers (including the input and output layers). But for some |
9,766 | What is the difference between convolutional neural networks and deep learning? | Within the fields of adaptive signal processing / machine learning, deep learning (DL) is a particular methodology in which we can train machines complex representations.
Generally, they will have a formulation that can map your input $\mathbf{x}$, all the way to the target objective, $\mathbf{y}$, via a series of hie... | What is the difference between convolutional neural networks and deep learning? | Within the fields of adaptive signal processing / machine learning, deep learning (DL) is a particular methodology in which we can train machines complex representations.
Generally, they will have a | What is the difference between convolutional neural networks and deep learning?
Within the fields of adaptive signal processing / machine learning, deep learning (DL) is a particular methodology in which we can train machines complex representations.
Generally, they will have a formulation that can map your input $\ma... | What is the difference between convolutional neural networks and deep learning?
Within the fields of adaptive signal processing / machine learning, deep learning (DL) is a particular methodology in which we can train machines complex representations.
Generally, they will have a |
9,767 | What is the difference between convolutional neural networks and deep learning? | Deep learning = deep artificial neural networks + other kind of deep models.
Deep artificial neural networks = artificial neural networks with more than 1 layer. (see minimum number of layers in a deep neural network or Wikipedia for more debate…)
Convolution Neural Network = A type of artificial neural networks | What is the difference between convolutional neural networks and deep learning? | Deep learning = deep artificial neural networks + other kind of deep models.
Deep artificial neural networks = artificial neural networks with more than 1 layer. (see minimum number of layers in a dee | What is the difference between convolutional neural networks and deep learning?
Deep learning = deep artificial neural networks + other kind of deep models.
Deep artificial neural networks = artificial neural networks with more than 1 layer. (see minimum number of layers in a deep neural network or Wikipedia for more d... | What is the difference between convolutional neural networks and deep learning?
Deep learning = deep artificial neural networks + other kind of deep models.
Deep artificial neural networks = artificial neural networks with more than 1 layer. (see minimum number of layers in a dee |
9,768 | What is the difference between convolutional neural networks and deep learning? | This slide by Yann LeCun makes the point that only models with a feature hierarchy (lower-level features are learned at one layer of a model, and then those features are combined at the next level) are deep.
A CNN can be deep or shallow; which is the case depends on whether it follows this "feature hierarchy" construct... | What is the difference between convolutional neural networks and deep learning? | This slide by Yann LeCun makes the point that only models with a feature hierarchy (lower-level features are learned at one layer of a model, and then those features are combined at the next level) ar | What is the difference between convolutional neural networks and deep learning?
This slide by Yann LeCun makes the point that only models with a feature hierarchy (lower-level features are learned at one layer of a model, and then those features are combined at the next level) are deep.
A CNN can be deep or shallow; wh... | What is the difference between convolutional neural networks and deep learning?
This slide by Yann LeCun makes the point that only models with a feature hierarchy (lower-level features are learned at one layer of a model, and then those features are combined at the next level) ar |
9,769 | What is the difference between convolutional neural networks and deep learning? | Deep learning is a general term for dealing with a complicated neural network with multiple layers. There is no standard definition of what exactly is deep. Usually, you can think a deep network is something that is too big for your laptop and PC to train. The data set would be so huge that you can't fit it into your m... | What is the difference between convolutional neural networks and deep learning? | Deep learning is a general term for dealing with a complicated neural network with multiple layers. There is no standard definition of what exactly is deep. Usually, you can think a deep network is so | What is the difference between convolutional neural networks and deep learning?
Deep learning is a general term for dealing with a complicated neural network with multiple layers. There is no standard definition of what exactly is deep. Usually, you can think a deep network is something that is too big for your laptop ... | What is the difference between convolutional neural networks and deep learning?
Deep learning is a general term for dealing with a complicated neural network with multiple layers. There is no standard definition of what exactly is deep. Usually, you can think a deep network is so |
9,770 | How to describe statistics in one sentence? | Statistics provides the reasoning and methods for producing and understanding data.
American Statistical Association | How to describe statistics in one sentence? | Statistics provides the reasoning and methods for producing and understanding data.
American Statistical Association | How to describe statistics in one sentence?
Statistics provides the reasoning and methods for producing and understanding data.
American Statistical Association | How to describe statistics in one sentence?
Statistics provides the reasoning and methods for producing and understanding data.
American Statistical Association |
9,771 | How to describe statistics in one sentence? | Statistics is fundamentally concerned with the understanding of structure in data.
Bill Venables and Brian Ripley, first sentence in Chapter 1 of Modern Applied Statistics with S | How to describe statistics in one sentence? | Statistics is fundamentally concerned with the understanding of structure in data.
Bill Venables and Brian Ripley, first sentence in Chapter 1 of Modern Applied Statistics with S | How to describe statistics in one sentence?
Statistics is fundamentally concerned with the understanding of structure in data.
Bill Venables and Brian Ripley, first sentence in Chapter 1 of Modern Applied Statistics with S | How to describe statistics in one sentence?
Statistics is fundamentally concerned with the understanding of structure in data.
Bill Venables and Brian Ripley, first sentence in Chapter 1 of Modern Applied Statistics with S |
9,772 | How to describe statistics in one sentence? | Statistics provides the reasoning and methods for converting data to meaningful information. | How to describe statistics in one sentence? | Statistics provides the reasoning and methods for converting data to meaningful information. | How to describe statistics in one sentence?
Statistics provides the reasoning and methods for converting data to meaningful information. | How to describe statistics in one sentence?
Statistics provides the reasoning and methods for converting data to meaningful information. |
9,773 | How to describe statistics in one sentence? | In the words of the late Leo Breiman:
The goals in statistics are to use data to predict and to get
information about the underlying data mechanism.
http://projecteuclid.org/euclid.ss/1009213726 | How to describe statistics in one sentence? | In the words of the late Leo Breiman:
The goals in statistics are to use data to predict and to get
information about the underlying data mechanism.
http://projecteuclid.org/euclid.ss/1009213726 | How to describe statistics in one sentence?
In the words of the late Leo Breiman:
The goals in statistics are to use data to predict and to get
information about the underlying data mechanism.
http://projecteuclid.org/euclid.ss/1009213726 | How to describe statistics in one sentence?
In the words of the late Leo Breiman:
The goals in statistics are to use data to predict and to get
information about the underlying data mechanism.
http://projecteuclid.org/euclid.ss/1009213726 |
9,774 | How to describe statistics in one sentence? | Personally, I like the following quote from Stephen Senn in Dicing with death. Chance, Risk and Health (Cambridge University Press, 2003). I highlighted one sentence (or two) that, I believe, summarize his main point, although the whole paragraph is worth reading.
Statistics are and statistics is.
Statistics, singul... | How to describe statistics in one sentence? | Personally, I like the following quote from Stephen Senn in Dicing with death. Chance, Risk and Health (Cambridge University Press, 2003). I highlighted one sentence (or two) that, I believe, summariz | How to describe statistics in one sentence?
Personally, I like the following quote from Stephen Senn in Dicing with death. Chance, Risk and Health (Cambridge University Press, 2003). I highlighted one sentence (or two) that, I believe, summarize his main point, although the whole paragraph is worth reading.
Statistics... | How to describe statistics in one sentence?
Personally, I like the following quote from Stephen Senn in Dicing with death. Chance, Risk and Health (Cambridge University Press, 2003). I highlighted one sentence (or two) that, I believe, summariz |
9,775 | How to describe statistics in one sentence? | Statistics is the science of learning from data and measuring, controlling, and communicating uncertainty.
Marie Davidian & Thomas Louis
They continue:
; and it thereby provides the navigation essential for controlling the course of scientific and societal advances | How to describe statistics in one sentence? | Statistics is the science of learning from data and measuring, controlling, and communicating uncertainty.
Marie Davidian & Thomas Louis
They continue:
; and it thereby provides the navigation essen | How to describe statistics in one sentence?
Statistics is the science of learning from data and measuring, controlling, and communicating uncertainty.
Marie Davidian & Thomas Louis
They continue:
; and it thereby provides the navigation essential for controlling the course of scientific and societal advances | How to describe statistics in one sentence?
Statistics is the science of learning from data and measuring, controlling, and communicating uncertainty.
Marie Davidian & Thomas Louis
They continue:
; and it thereby provides the navigation essen |
9,776 | How to describe statistics in one sentence? | Statistics is a kitbag of methods and modes of thought that help people to make clear conclusions from noisy information. | How to describe statistics in one sentence? | Statistics is a kitbag of methods and modes of thought that help people to make clear conclusions from noisy information. | How to describe statistics in one sentence?
Statistics is a kitbag of methods and modes of thought that help people to make clear conclusions from noisy information. | How to describe statistics in one sentence?
Statistics is a kitbag of methods and modes of thought that help people to make clear conclusions from noisy information. |
9,777 | How to describe statistics in one sentence? | Because we are not a godlike all-knowing creature we have to deal with uncertainty and Statistics provides methods to incorporate and reflect that uncertainty. | How to describe statistics in one sentence? | Because we are not a godlike all-knowing creature we have to deal with uncertainty and Statistics provides methods to incorporate and reflect that uncertainty. | How to describe statistics in one sentence?
Because we are not a godlike all-knowing creature we have to deal with uncertainty and Statistics provides methods to incorporate and reflect that uncertainty. | How to describe statistics in one sentence?
Because we are not a godlike all-knowing creature we have to deal with uncertainty and Statistics provides methods to incorporate and reflect that uncertainty. |
9,778 | How to describe statistics in one sentence? | statistics is a sub-field of philosophy that deals with the following question 'how we learn from observations' using rigorous mathematical concepts.
just a side note you can make 'one sentence' very long, there is a book written by B. Hrabal that consist of one long sentence, see:
Dancing Lessons for the Advanced in A... | How to describe statistics in one sentence? | statistics is a sub-field of philosophy that deals with the following question 'how we learn from observations' using rigorous mathematical concepts.
just a side note you can make 'one sentence' very | How to describe statistics in one sentence?
statistics is a sub-field of philosophy that deals with the following question 'how we learn from observations' using rigorous mathematical concepts.
just a side note you can make 'one sentence' very long, there is a book written by B. Hrabal that consist of one long sentence... | How to describe statistics in one sentence?
statistics is a sub-field of philosophy that deals with the following question 'how we learn from observations' using rigorous mathematical concepts.
just a side note you can make 'one sentence' very |
9,779 | How to describe statistics in one sentence? | Statistics is both the science of uncertainty and the technology of
extracting information from data
David J. Hand | How to describe statistics in one sentence? | Statistics is both the science of uncertainty and the technology of
extracting information from data
David J. Hand | How to describe statistics in one sentence?
Statistics is both the science of uncertainty and the technology of
extracting information from data
David J. Hand | How to describe statistics in one sentence?
Statistics is both the science of uncertainty and the technology of
extracting information from data
David J. Hand |
9,780 | How to describe statistics in one sentence? | Statistics is a set of logical principles and mathematical methods for summarizing quantified information in accurate, relevant ways. | How to describe statistics in one sentence? | Statistics is a set of logical principles and mathematical methods for summarizing quantified information in accurate, relevant ways. | How to describe statistics in one sentence?
Statistics is a set of logical principles and mathematical methods for summarizing quantified information in accurate, relevant ways. | How to describe statistics in one sentence?
Statistics is a set of logical principles and mathematical methods for summarizing quantified information in accurate, relevant ways. |
9,781 | How to describe statistics in one sentence? | In my own words
Statistics is the science of what might be
This is sort of tongue-in-cheek. | How to describe statistics in one sentence? | In my own words
Statistics is the science of what might be
This is sort of tongue-in-cheek. | How to describe statistics in one sentence?
In my own words
Statistics is the science of what might be
This is sort of tongue-in-cheek. | How to describe statistics in one sentence?
In my own words
Statistics is the science of what might be
This is sort of tongue-in-cheek. |
9,782 | How to describe statistics in one sentence? | Fisher (1922) gave his view on the essence of statistics in the following quote (bold font added by me for the one sentence requirement):
In order to arrive at a distinct formulation of statistical problems, it is necessary to define the task which the statistician sets himself: briefly, and in its most concrete form,... | How to describe statistics in one sentence? | Fisher (1922) gave his view on the essence of statistics in the following quote (bold font added by me for the one sentence requirement):
In order to arrive at a distinct formulation of statistical p | How to describe statistics in one sentence?
Fisher (1922) gave his view on the essence of statistics in the following quote (bold font added by me for the one sentence requirement):
In order to arrive at a distinct formulation of statistical problems, it is necessary to define the task which the statistician sets hims... | How to describe statistics in one sentence?
Fisher (1922) gave his view on the essence of statistics in the following quote (bold font added by me for the one sentence requirement):
In order to arrive at a distinct formulation of statistical p |
9,783 | How to describe statistics in one sentence? | A results-oriented (and so not really descriptive) one-liner would be, for me,
Statistics is what makes the human world go round, irrespective of what is that does the same for Nature. | How to describe statistics in one sentence? | A results-oriented (and so not really descriptive) one-liner would be, for me,
Statistics is what makes the human world go round, irrespective of what is that does the same for Nature. | How to describe statistics in one sentence?
A results-oriented (and so not really descriptive) one-liner would be, for me,
Statistics is what makes the human world go round, irrespective of what is that does the same for Nature. | How to describe statistics in one sentence?
A results-oriented (and so not really descriptive) one-liner would be, for me,
Statistics is what makes the human world go round, irrespective of what is that does the same for Nature. |
9,784 | How to describe statistics in one sentence? | Statistics is a tool for modeling the generation of data by uncertain and/or probabilistic processes. | How to describe statistics in one sentence? | Statistics is a tool for modeling the generation of data by uncertain and/or probabilistic processes. | How to describe statistics in one sentence?
Statistics is a tool for modeling the generation of data by uncertain and/or probabilistic processes. | How to describe statistics in one sentence?
Statistics is a tool for modeling the generation of data by uncertain and/or probabilistic processes. |
9,785 | How to describe statistics in one sentence? | A name for functions of the results of observations.
from here.
This is the meaning closest to that of OP. He's not talking about the branch of science. He means statistics such as mean and median. These are the functions on data | How to describe statistics in one sentence? | A name for functions of the results of observations.
from here.
This is the meaning closest to that of OP. He's not talking about the branch of science. He means statistics such as mean and median. T | How to describe statistics in one sentence?
A name for functions of the results of observations.
from here.
This is the meaning closest to that of OP. He's not talking about the branch of science. He means statistics such as mean and median. These are the functions on data | How to describe statistics in one sentence?
A name for functions of the results of observations.
from here.
This is the meaning closest to that of OP. He's not talking about the branch of science. He means statistics such as mean and median. T |
9,786 | How to describe statistics in one sentence? | Statistics is about torturing data long enough until it confess anything you want to show.
I am paraphrasing Ronald Coase, see link | How to describe statistics in one sentence? | Statistics is about torturing data long enough until it confess anything you want to show.
I am paraphrasing Ronald Coase, see link | How to describe statistics in one sentence?
Statistics is about torturing data long enough until it confess anything you want to show.
I am paraphrasing Ronald Coase, see link | How to describe statistics in one sentence?
Statistics is about torturing data long enough until it confess anything you want to show.
I am paraphrasing Ronald Coase, see link |
9,787 | How to describe statistics in one sentence? | Statistics is the mathematical science that allows you to figure out if the difference between sets of observations are just random or not. | How to describe statistics in one sentence? | Statistics is the mathematical science that allows you to figure out if the difference between sets of observations are just random or not. | How to describe statistics in one sentence?
Statistics is the mathematical science that allows you to figure out if the difference between sets of observations are just random or not. | How to describe statistics in one sentence?
Statistics is the mathematical science that allows you to figure out if the difference between sets of observations are just random or not. |
9,788 | Compute a cosine dissimilarity matrix in R [closed] | As @Max indicated in the comments (+1) it would be simpler to "write your own" than to spend time looking for it somewhere else. As we know, the cosine similarity between two vectors $A,B$ of length $n$ is
$$
C = \frac{ \sum \limits_{i=1}^{n}A_{i} B_{i} }{ \sqrt{\sum \limits_{i=1}^{n} A_{i}^2} \cdot \sqrt{\sum \limit... | Compute a cosine dissimilarity matrix in R [closed] | As @Max indicated in the comments (+1) it would be simpler to "write your own" than to spend time looking for it somewhere else. As we know, the cosine similarity between two vectors $A,B$ of length $ | Compute a cosine dissimilarity matrix in R [closed]
As @Max indicated in the comments (+1) it would be simpler to "write your own" than to spend time looking for it somewhere else. As we know, the cosine similarity between two vectors $A,B$ of length $n$ is
$$
C = \frac{ \sum \limits_{i=1}^{n}A_{i} B_{i} }{ \sqrt{\sum... | Compute a cosine dissimilarity matrix in R [closed]
As @Max indicated in the comments (+1) it would be simpler to "write your own" than to spend time looking for it somewhere else. As we know, the cosine similarity between two vectors $A,B$ of length $ |
9,789 | Compute a cosine dissimilarity matrix in R [closed] | Many answers here are computationally inefficient, try this;
For cosine similarity matrix
Matrix <- as.matrix(DF)
sim <- Matrix / sqrt(rowSums(Matrix * Matrix))
sim <- sim %*% t(sim)
Convert to cosine dissimilarity matrix (distance matrix).
D_sim <- as.dist(1 - sim) | Compute a cosine dissimilarity matrix in R [closed] | Many answers here are computationally inefficient, try this;
For cosine similarity matrix
Matrix <- as.matrix(DF)
sim <- Matrix / sqrt(rowSums(Matrix * Matrix))
sim <- sim %*% t(sim)
Convert to cosi | Compute a cosine dissimilarity matrix in R [closed]
Many answers here are computationally inefficient, try this;
For cosine similarity matrix
Matrix <- as.matrix(DF)
sim <- Matrix / sqrt(rowSums(Matrix * Matrix))
sim <- sim %*% t(sim)
Convert to cosine dissimilarity matrix (distance matrix).
D_sim <- as.dist(1 - sim) | Compute a cosine dissimilarity matrix in R [closed]
Many answers here are computationally inefficient, try this;
For cosine similarity matrix
Matrix <- as.matrix(DF)
sim <- Matrix / sqrt(rowSums(Matrix * Matrix))
sim <- sim %*% t(sim)
Convert to cosi |
9,790 | Compute a cosine dissimilarity matrix in R [closed] | You can use the cosine function from the lsa package:
http://cran.r-project.org/web/packages/lsa | Compute a cosine dissimilarity matrix in R [closed] | You can use the cosine function from the lsa package:
http://cran.r-project.org/web/packages/lsa | Compute a cosine dissimilarity matrix in R [closed]
You can use the cosine function from the lsa package:
http://cran.r-project.org/web/packages/lsa | Compute a cosine dissimilarity matrix in R [closed]
You can use the cosine function from the lsa package:
http://cran.r-project.org/web/packages/lsa |
9,791 | Compute a cosine dissimilarity matrix in R [closed] | The following function might be useful when working with matrices, instead of 1-d vectors:
# input: row matrices 'ma' and 'mb' (with compatible dimensions)
# output: cosine similarity matrix
cos.sim=function(ma, mb){
mat=tcrossprod(ma, mb)
t1=sqrt(apply(ma, 1, crossprod))
t2=sqrt(apply(mb, 1, crossprod))
mat /... | Compute a cosine dissimilarity matrix in R [closed] | The following function might be useful when working with matrices, instead of 1-d vectors:
# input: row matrices 'ma' and 'mb' (with compatible dimensions)
# output: cosine similarity matrix
cos.sim= | Compute a cosine dissimilarity matrix in R [closed]
The following function might be useful when working with matrices, instead of 1-d vectors:
# input: row matrices 'ma' and 'mb' (with compatible dimensions)
# output: cosine similarity matrix
cos.sim=function(ma, mb){
mat=tcrossprod(ma, mb)
t1=sqrt(apply(ma, 1, cr... | Compute a cosine dissimilarity matrix in R [closed]
The following function might be useful when working with matrices, instead of 1-d vectors:
# input: row matrices 'ma' and 'mb' (with compatible dimensions)
# output: cosine similarity matrix
cos.sim= |
9,792 | Compute a cosine dissimilarity matrix in R [closed] | Ramping up some of the previous code (from @Macro) on this issue, we can wrap this into a cleaner version in the following:
df <- data.frame(t(data.frame(c1=rnorm(100),
c2=rnorm(100),
c3=rnorm(100),
c4=rnorm(100),
... | Compute a cosine dissimilarity matrix in R [closed] | Ramping up some of the previous code (from @Macro) on this issue, we can wrap this into a cleaner version in the following:
df <- data.frame(t(data.frame(c1=rnorm(100),
c | Compute a cosine dissimilarity matrix in R [closed]
Ramping up some of the previous code (from @Macro) on this issue, we can wrap this into a cleaner version in the following:
df <- data.frame(t(data.frame(c1=rnorm(100),
c2=rnorm(100),
c3=rnorm(100),
... | Compute a cosine dissimilarity matrix in R [closed]
Ramping up some of the previous code (from @Macro) on this issue, we can wrap this into a cleaner version in the following:
df <- data.frame(t(data.frame(c1=rnorm(100),
c |
9,793 | Do error bars on probabilities have any meaning? | It wouldn't make sense if you were talking about known probabilities, e.g. with fair coin the probability of throwing heads is 0.5 by definition. However, unless you are talking about textbook example, the exact probability is never known, we only know it approximately.
The different story is when you estimate the prob... | Do error bars on probabilities have any meaning? | It wouldn't make sense if you were talking about known probabilities, e.g. with fair coin the probability of throwing heads is 0.5 by definition. However, unless you are talking about textbook example | Do error bars on probabilities have any meaning?
It wouldn't make sense if you were talking about known probabilities, e.g. with fair coin the probability of throwing heads is 0.5 by definition. However, unless you are talking about textbook example, the exact probability is never known, we only know it approximately.
... | Do error bars on probabilities have any meaning?
It wouldn't make sense if you were talking about known probabilities, e.g. with fair coin the probability of throwing heads is 0.5 by definition. However, unless you are talking about textbook example |
9,794 | Do error bars on probabilities have any meaning? | A most relevant illustration from xkcd:
with associated caption:
...an effect size of 1.68 (95% CI: 1.56 (95% CI: 1.52 (95% CI: 1.504
(95% CI: 1.494 (95% CI: 1.488 (95% CI: 1.485 (95% CI: 1.482 (95% CI:
1.481 (95% CI: 1.4799 (95% CI: 1.4791 (95% CI: 1.4784... | Do error bars on probabilities have any meaning? | A most relevant illustration from xkcd:
with associated caption:
...an effect size of 1.68 (95% CI: 1.56 (95% CI: 1.52 (95% CI: 1.504
(95% CI: 1.494 (95% CI: 1.488 (95% CI: 1.485 (95% CI: 1.482 (9 | Do error bars on probabilities have any meaning?
A most relevant illustration from xkcd:
with associated caption:
...an effect size of 1.68 (95% CI: 1.56 (95% CI: 1.52 (95% CI: 1.504
(95% CI: 1.494 (95% CI: 1.488 (95% CI: 1.485 (95% CI: 1.482 (95% CI:
1.481 (95% CI: 1.4799 (95% CI: 1.4791 (95% CI: 1.4784... | Do error bars on probabilities have any meaning?
A most relevant illustration from xkcd:
with associated caption:
...an effect size of 1.68 (95% CI: 1.56 (95% CI: 1.52 (95% CI: 1.504
(95% CI: 1.494 (95% CI: 1.488 (95% CI: 1.485 (95% CI: 1.482 (9 |
9,795 | Do error bars on probabilities have any meaning? | I know of two interpretations. The first was said by Tim: We have observed $X$ successes out of $Y$ trials, so if we believe the trials were i.i.d. we can estimate the probability of the process at $X/Y$ with some error bars, e.g. of order $1/\sqrt{Y}$.
The second involves "higher-order probabilities" or uncertainties ... | Do error bars on probabilities have any meaning? | I know of two interpretations. The first was said by Tim: We have observed $X$ successes out of $Y$ trials, so if we believe the trials were i.i.d. we can estimate the probability of the process at $X | Do error bars on probabilities have any meaning?
I know of two interpretations. The first was said by Tim: We have observed $X$ successes out of $Y$ trials, so if we believe the trials were i.i.d. we can estimate the probability of the process at $X/Y$ with some error bars, e.g. of order $1/\sqrt{Y}$.
The second involv... | Do error bars on probabilities have any meaning?
I know of two interpretations. The first was said by Tim: We have observed $X$ successes out of $Y$ trials, so if we believe the trials were i.i.d. we can estimate the probability of the process at $X |
9,796 | Do error bars on probabilities have any meaning? | All measurements are uncertain.
Therefore, any measurement of probability is also uncertain.
This uncertainty on the measurement of probability can be visually represented with an uncertainty bar. Note that uncertainty bars are often referred to as error bars. This is incorrect or at least misleading, because it show... | Do error bars on probabilities have any meaning? | All measurements are uncertain.
Therefore, any measurement of probability is also uncertain.
This uncertainty on the measurement of probability can be visually represented with an uncertainty bar. No | Do error bars on probabilities have any meaning?
All measurements are uncertain.
Therefore, any measurement of probability is also uncertain.
This uncertainty on the measurement of probability can be visually represented with an uncertainty bar. Note that uncertainty bars are often referred to as error bars. This is ... | Do error bars on probabilities have any meaning?
All measurements are uncertain.
Therefore, any measurement of probability is also uncertain.
This uncertainty on the measurement of probability can be visually represented with an uncertainty bar. No |
9,797 | Do error bars on probabilities have any meaning? | How could an error bar on a probability arise? Suppose we can assign $\mathrm{prob}(\mathcal{A} | \Theta = \theta, \mathcal{I})$. If $\mathcal{I}$ implies $\Theta = \theta_0$, then $\mathrm{prob}(\Theta = \theta | \mathcal{I}) = \delta_{\theta \theta_0}$ and
\begin{align}
\mathrm{prob}(\mathcal{A} | \mathcal{I}) &= \su... | Do error bars on probabilities have any meaning? | How could an error bar on a probability arise? Suppose we can assign $\mathrm{prob}(\mathcal{A} | \Theta = \theta, \mathcal{I})$. If $\mathcal{I}$ implies $\Theta = \theta_0$, then $\mathrm{prob}(\The | Do error bars on probabilities have any meaning?
How could an error bar on a probability arise? Suppose we can assign $\mathrm{prob}(\mathcal{A} | \Theta = \theta, \mathcal{I})$. If $\mathcal{I}$ implies $\Theta = \theta_0$, then $\mathrm{prob}(\Theta = \theta | \mathcal{I}) = \delta_{\theta \theta_0}$ and
\begin{align... | Do error bars on probabilities have any meaning?
How could an error bar on a probability arise? Suppose we can assign $\mathrm{prob}(\mathcal{A} | \Theta = \theta, \mathcal{I})$. If $\mathcal{I}$ implies $\Theta = \theta_0$, then $\mathrm{prob}(\The |
9,798 | Do error bars on probabilities have any meaning? | There are very often occasions where you want to have a probability of a probability. Say for instance you worked in food safety and used a survival analysis model to estimate the probability that botulinum spores would germinate (and thus produce the deadly toxin) as a function of the food preparation steps (i.e. coo... | Do error bars on probabilities have any meaning? | There are very often occasions where you want to have a probability of a probability. Say for instance you worked in food safety and used a survival analysis model to estimate the probability that bo | Do error bars on probabilities have any meaning?
There are very often occasions where you want to have a probability of a probability. Say for instance you worked in food safety and used a survival analysis model to estimate the probability that botulinum spores would germinate (and thus produce the deadly toxin) as a... | Do error bars on probabilities have any meaning?
There are very often occasions where you want to have a probability of a probability. Say for instance you worked in food safety and used a survival analysis model to estimate the probability that bo |
9,799 | Do error bars on probabilities have any meaning? | tl;dr- Any one-off guess from a particular guesser can be reduced to a single probability. However, that's just the trivial case; probability structures can make sense whenever there's some contextual relevance beyond just a single probability.
The chance of a random coin landing on Heads is 50%.
Doesn't matter if i... | Do error bars on probabilities have any meaning? | tl;dr- Any one-off guess from a particular guesser can be reduced to a single probability. However, that's just the trivial case; probability structures can make sense whenever there's some contextu | Do error bars on probabilities have any meaning?
tl;dr- Any one-off guess from a particular guesser can be reduced to a single probability. However, that's just the trivial case; probability structures can make sense whenever there's some contextual relevance beyond just a single probability.
The chance of a random ... | Do error bars on probabilities have any meaning?
tl;dr- Any one-off guess from a particular guesser can be reduced to a single probability. However, that's just the trivial case; probability structures can make sense whenever there's some contextu |
9,800 | Do error bars on probabilities have any meaning? | I would argue that only the error bars matter, but in the given example, the whole thing is probably almost meaningless.
The example lends itself to interpretaton as a confidence interval, in which the upper and lower bounds of some degree of certainty are the range of probability. This proposed answer will deal with ... | Do error bars on probabilities have any meaning? | I would argue that only the error bars matter, but in the given example, the whole thing is probably almost meaningless.
The example lends itself to interpretaton as a confidence interval, in which th | Do error bars on probabilities have any meaning?
I would argue that only the error bars matter, but in the given example, the whole thing is probably almost meaningless.
The example lends itself to interpretaton as a confidence interval, in which the upper and lower bounds of some degree of certainty are the range of p... | Do error bars on probabilities have any meaning?
I would argue that only the error bars matter, but in the given example, the whole thing is probably almost meaningless.
The example lends itself to interpretaton as a confidence interval, in which th |
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