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433 | 2 | null | 423 | 73 | null | Here's [another one from Dilbert](http://dilbert.com/strips/comic/2010-07-02/):
| null | CC BY-SA 3.0 | null | 2010-07-21T15:43:44.457 | 2015-02-24T20:50:13.917 | 2015-02-24T20:50:13.917 | 7290 | 5 | null |
434 | 2 | null | 22 | 85 | null | Very crudely I would say that:
Frequentist: Sampling is infinite and decision rules can be sharp. Data are a repeatable random sample - there is a frequency. Underlying parameters are fixed i.e. they remain constant during this repeatable sampling process.
Bayesian: Unknown quantities are treated probabilistically and... | null | CC BY-SA 4.0 | null | 2010-07-21T15:50:43.377 | 2020-04-03T14:53:28.790 | 2020-06-11T14:32:37.003 | -1 | 215 | null |
435 | 2 | null | 423 | 197 | null | One more [Dilbert cartoon](http://dilbert.com/fast/2008-05-08/):
...
| null | CC BY-SA 3.0 | null | 2010-07-21T15:53:59.553 | 2015-02-05T11:28:02.847 | 2017-03-09T17:30:36.203 | -1 | null | null |
436 | 2 | null | 421 | 24 | null | The answer would most definitely depend on their discipline, the methods/techniques that they would like to learn and their existing mathematical/statistical abilities.
For example, economists/social scientists who want to learn about cutting edge empirical econometrics could read Angrist and Pischke's [Mostly Harmless... | null | CC BY-SA 2.5 | null | 2010-07-21T16:04:18.627 | 2010-08-11T08:46:15.107 | 2010-08-11T08:46:15.107 | 509 | 215 | null |
437 | 2 | null | 414 | 5 | null | For you I would suggest:
[Introduction to the Mathematical and Statistical Foundations of Econometrics](https://www.cambridge.org/core/books/introduction-to-the-mathematical-and-statistical-foundations-of-econometrics/0AB780F0657A93807188838B1E7C529A) by Herman J. Bierens, CUP. The word "Introduction" in the title is a... | null | CC BY-SA 4.0 | null | 2010-07-21T16:07:20.810 | 2023-02-11T10:07:35.567 | 2023-02-11T10:07:35.567 | 362671 | 215 | null |
438 | 2 | null | 165 | 33 | null | OK here's my best attempt at an informal and crude explanation.
A Markov Chain is a random process that has the property that the future depends only on the current state of the process and not the past i.e. it is memoryless. An example of a random process could be the stock exchange. An example of a Markov Chain would... | null | CC BY-SA 2.5 | null | 2010-07-21T16:42:43.820 | 2010-07-21T16:42:43.820 | null | null | 215 | null |
439 | 2 | null | 414 | 28 | null | As you said, it's not necessarily the case that a mathematician may want a rigorous book. Maybe the goal is to get some intuition of the concepts quickly, and then fill in the details. I recommend two books from CMU professors, both published by Springer: "[All of Statistics](https://link.springer.com/book/10.1007/978-... | null | CC BY-SA 4.0 | null | 2010-07-21T16:50:35.697 | 2023-02-11T10:15:04.673 | 2023-02-11T10:15:04.673 | 362671 | 30 | null |
440 | 2 | null | 421 | 21 | null | [Peter Dalgaard's Introductory Statistics with R](http://rads.stackoverflow.com/amzn/click/0387790535) is a great book for some introductory statistics with a focus on the R software for data analysis.
| null | CC BY-SA 2.5 | null | 2010-07-21T16:53:35.677 | 2010-07-21T16:53:35.677 | null | null | 36 | null |
441 | 2 | null | 290 | 5 | null | UCLA has the best free resources you'll find anywhere.
[https://stats.idre.ucla.edu/stata/](https://stats.idre.ucla.edu/stata/)
| null | CC BY-SA 3.0 | null | 2010-07-21T16:54:38.483 | 2017-10-12T15:20:16.267 | 2017-10-12T15:20:16.267 | 27422 | 36 | null |
442 | 2 | null | 363 | 8 | null | I say the [visual display of quantitative information](http://rads.stackoverflow.com/amzn/click/0961392142) by Tufte, and [Freakonomics](http://rads.stackoverflow.com/amzn/click/0060731338) for something fun.
| null | CC BY-SA 2.5 | null | 2010-07-21T16:56:45.453 | 2010-07-21T16:56:45.453 | null | null | 36 | null |
443 | 2 | null | 36 | 11 | null | There's two aspects to this post hoc ergo propter hoc problem that I like to cover: (i) reverse causality and (ii) endogeneity
An example of "possible" reverse causality:
Social drinking and earnings - drinkers earn more money according to Bethany L. Peters & Edward Stringham (2006. "No Booze? You May Lose: Why Drinke... | null | CC BY-SA 3.0 | null | 2010-07-21T17:06:32.303 | 2012-03-31T10:45:48.593 | 2012-03-31T10:45:48.593 | 9007 | 215 | null |
445 | 2 | null | 290 | 5 | null | The UCLA resource listed by Stephen Turner (below) is excellent if you just want to apply methods you're already familiar with using Stata.
If you're looking for textbooks which teach you statistics/econometrics while using Stata then these are solid recommendations (but it depends at what level you're looking at):
Int... | null | CC BY-SA 3.0 | null | 2010-07-21T17:13:33.117 | 2017-10-12T11:29:26.230 | 2017-10-12T11:29:26.230 | 27422 | 215 | null |
446 | 2 | null | 125 | 18 | null | The Gelman books are all excellent but not necessarily introductory in that they assume that you know some statistics already. Therefore they are an introduction to the Bayesian way of doing statistics rather than to statistics in general. I would still give them the thumbs up, however.
As an introductory statistics/ec... | null | CC BY-SA 3.0 | null | 2010-07-21T17:17:45.780 | 2012-07-24T05:47:17.923 | 2012-07-24T05:47:17.923 | 9007 | 215 | null |
447 | 2 | null | 170 | 11 | null | I really like these two books by Daniel McFadden of Berkeley:
- Lecture Notes: Econometric Tools
http://elsa.berkeley.edu/users/mcfadden/e240a_sp98/e240a.html
- Lecture Notes: Econometrics/Statistics http://elsa.berkeley.edu/users/mcfadden/e240b_f01/e240b.html
| null | CC BY-SA 4.0 | null | 2010-07-21T17:26:14.377 | 2020-09-23T05:50:43.943 | 2020-09-23T05:50:43.943 | 17760 | 215 | null |
448 | 2 | null | 396 | 6 | null | Here are my guidelines, based on the most common errors I see (in addition to all the other good points mentioned)
- Use scatter graphs, not line plots, if element order is not relevant.
- When preparing plots that are meant to be compared, use the same scale factor for all of them.
- Even better - find a way to com... | null | CC BY-SA 4.0 | null | 2010-07-21T17:26:15.483 | 2022-11-23T09:56:13.210 | 2022-11-23T09:56:13.210 | 362671 | 77 | null |
449 | 2 | null | 328 | 1 | null | More from an economics perspectives I think these two sets of lecture notes are very good:
[http://home.datacomm.ch/paulsoderlind/Courses/OldCourses/FinEcmtAll.pdf](http://home.datacomm.ch/paulsoderlind/Courses/OldCourses/FinEcmtAll.pdf)
[http://personal.lse.ac.uk/mele/files/fin_eco.pdf](http://personal.lse.ac.uk/mele/... | null | CC BY-SA 2.5 | null | 2010-07-21T17:28:57.803 | 2010-07-21T17:28:57.803 | null | null | 215 | null |
450 | 2 | null | 418 | 8 | null | For us, it is just one example of a robust regression -- I believe it is used by statisticians also, but maybe not so wide because it has some better known alternatives.
| null | CC BY-SA 2.5 | null | 2010-07-21T17:30:02.077 | 2010-07-21T17:30:02.077 | null | null | null | null |
451 | 2 | null | 26 | 6 | null | When describing a variable we typically summarise it using two measures: a measure of centre and a measure of spread. Common measures of centre include the mean, median and mode. Common measure of spread include the variance and interquartile range.
The variance (represented by the Greek lowercase sigma raised to the p... | null | CC BY-SA 3.0 | null | 2010-07-21T17:38:08.583 | 2013-04-20T01:19:50.947 | 2013-04-20T01:19:50.947 | 24560 | 215 | null |
452 | 1 | 711 | null | 25 | 67691 | It has been suggested by Angrist and Pischke that Robust (i.e. robust to heteroskedasticity or unequal variances) Standard Errors are reported as a matter of course rather than testing for it. Two questions:
- What is impact on the standard errors of doing so when there is homoskedasticity?
- Does anybody actually do... | Always Report Robust (White) Standard Errors? | CC BY-SA 2.5 | null | 2010-07-21T17:45:01.570 | 2019-12-27T02:55:23.200 | 2017-02-13T10:08:10.600 | 28666 | 215 | [
"regression",
"standard-error",
"heteroscedasticity",
"robust-standard-error"
] |
453 | 2 | null | 421 | 9 | null | [Statistics in Plain English](http://rads.stackoverflow.com/amzn/click/041587291X) is pretty good.
4.5 on Amazon, 11 reviews.
Explains ANOVA pretty well too.
| null | CC BY-SA 2.5 | null | 2010-07-21T17:54:05.170 | 2010-07-21T17:54:05.170 | null | null | 74 | null |
454 | 2 | null | 396 | 1 | null | It depends on the way in which the plots will be discussed.
For instance, if I'm sending out plots for a group meeting that will be done with callers from different locations, I prefer putting them together in Powerpoint as opposed to Excel, so it's easier to flip around.
For one-on-one technical calls, I'll put some... | null | CC BY-SA 2.5 | null | 2010-07-21T18:11:59.113 | 2010-07-21T18:11:59.113 | null | null | 62 | null |
455 | 2 | null | 423 | 47 | null | Allright, I think this one is hilarious- but let's see if it passes the Statistical Analysis Miller test.
## Fermirotica
[](http://xkcd.com/563/)
>
I love how Google handles dimensional analysis. Stats are ballpark and vary wildly by time of day and whether your mom is in town.
| null | CC BY-SA 2.5 | null | 2010-07-21T18:18:13.170 | 2010-07-23T15:27:06.463 | 2017-03-09T17:30:36.220 | -1 | 13 | null |
456 | 2 | null | 277 | 19 | null | As the [Encyclopedia of GIS](http://books.google.com/books?id=6q2lOfLnwkAC&dq=Encyclopedia+of+GIS) states, the conditional autoregressive model (CAR) is appropriate for situations with first order dependency or relatively local spatial autocorrelation, and simultaneous autoregressive model (SAR) is more suitable where... | null | CC BY-SA 2.5 | null | 2010-07-21T18:26:02.873 | 2010-07-27T19:11:57.330 | 2010-07-27T19:11:57.330 | 39 | 39 | null |
457 | 2 | null | 359 | 5 | null | I do not know the literature in the area well enough to offer a direct response. However, it seems to me that if the three tests differ then that is an indication that you need further research/data collection in order to definitively answer your question.
You may also want to look at [this](http://scholar.google.com/... | null | CC BY-SA 2.5 | null | 2010-07-21T18:28:27.423 | 2010-07-22T01:21:24.837 | 2010-07-22T01:21:24.837 | null | null | null |
458 | 2 | null | 194 | 3 | null | One way to test patterns in stock market data is discussed [here](http://www.evidencebasedta.com/). A similar approach would be to randomise the stock market data and identify your patterns of interest, which would obviously be devoid of any meaning due to the deliberate randomising process. These randomly generated pa... | null | CC BY-SA 2.5 | null | 2010-07-21T18:41:12.033 | 2010-07-21T18:41:12.033 | null | null | 226 | null |
459 | 1 | 479 | null | 9 | 1075 | We're plotting time-series metrics in the context of network/server operations. The data has a 5-minute sample rate, and consists of things like CPU utilization, error rate, etc.
We're adding a horizontal "threshold" line to the graphs, to visually indicate a value threshold above which people should worry/take notice.... | Good line color for "threshold" line in a time-series graph? | CC BY-SA 3.0 | null | 2010-07-21T19:59:48.020 | 2013-05-15T04:14:18.790 | 2013-05-15T04:14:18.790 | 805 | 259 | [
"time-series",
"data-visualization"
] |
460 | 2 | null | 213 | 7 | null | For moderate dimensions, like 3, then some sort of kernel cross-validation technique as suggested elsewhere seems reasonable and is the best I can come up with.
For higher dimensions, I'm not sure that the problem is solvable; it lands pretty squarely into 'curse-of-dimensionality' territory. The issue is that distanc... | null | CC BY-SA 2.5 | null | 2010-07-21T20:03:40.367 | 2010-07-21T20:03:40.367 | null | null | 61 | null |
461 | 2 | null | 459 | 4 | null | To me, whether or not the line represents actual data seems irrelevant. What's the point of the plot? If it's so that somebody will do something when utilization crosses a threshold, the line marking the threshold had better be very visible. If the point of the plot is to give an overview of utilization over time, t... | null | CC BY-SA 2.5 | null | 2010-07-21T20:07:32.057 | 2010-07-21T20:07:32.057 | null | null | 71 | null |
462 | 2 | null | 396 | 9 | null | In the physics field there is a rule that the whole paper/report should be understandable only from quick look at the plots. So I would mainly advise that they should be self-explanatory.
This also implies that you must always check whether your audience is familiar with some kind of plot -- I had once made a big mista... | null | CC BY-SA 3.0 | null | 2010-07-21T20:11:02.580 | 2016-09-17T13:45:15.090 | 2016-09-17T13:45:15.090 | 22047 | null | null |
463 | 2 | null | 363 | 7 | null | In addition to "The History of Statistics" suggested by Graham, another Stigler book worth reading is
[Statistics on the Table: The History of Statistical Concepts and Methods](http://rads.stackoverflow.com/amzn/click/0674009797)
| null | CC BY-SA 2.5 | null | 2010-07-21T20:29:12.783 | 2010-07-21T20:29:12.783 | null | null | 90 | null |
464 | 2 | null | 459 | 3 | null | If this is about your "Qnotifier" I think that you should plot the threshold line in some darker gray so it is distinguishable but not disturbing. Then I would color the part of the plot that reaches over the threshold in some alarmistic hue, like red.
| null | CC BY-SA 2.5 | null | 2010-07-21T20:34:43.147 | 2010-07-21T20:34:43.147 | null | null | null | null |
465 | 2 | null | 452 | 3 | null | I thought that the White Standard Error and the Standard Error computed in the "normal" way (eg, Hessian and/or OPG in the case of maximum likelihood) were asymptotically equivalent in the case of homoskedasticity?
Only if there is heteroskedasticity will the "normal" standard error be inappropriate, which means that ... | null | CC BY-SA 2.5 | null | 2010-07-21T20:45:08.177 | 2010-07-21T20:45:08.177 | null | null | 90 | null |
466 | 2 | null | 170 | 12 | null | Not Statistics specific, but a good resource is: [http://www.reddit.com/r/mathbooks](http://www.reddit.com/r/mathbooks)
Also, George Cain at Georgia Tech maintains a list of freely available maths texts that includes some statistical texts. [http://people.math.gatech.edu/~cain/textbooks/onlinebooks.html](http://peopl... | null | CC BY-SA 2.5 | null | 2010-07-21T20:53:54.800 | 2010-07-21T20:53:54.800 | null | null | 115 | null |
467 | 2 | null | 7 | 7 | null | [http://www.reddit.com/r/datasets](http://www.reddit.com/r/datasets) and also, [http://www.reddit.com/r/opendata](http://www.reddit.com/r/opendata) both contain a constantly growing list of pointers to various datasets.
| null | CC BY-SA 2.5 | null | 2010-07-21T21:04:03.950 | 2010-07-21T21:04:03.950 | null | null | 115 | null |
468 | 2 | null | 124 | 4 | null | If you're coming from the programming side, one option is to use the [Natural Language Toolkit](http://www.nltrk.org) (NLTK) for Python. There's an O'Reilly book, [available freely](http://www.nltk.org/book), which might be a less dense and more practical introduction to building classifiers for documents among other ... | null | CC BY-SA 2.5 | null | 2010-07-21T22:05:04.773 | 2010-07-21T22:05:04.773 | null | null | 251 | null |
470 | 2 | null | 170 | 63 | null | The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman is a standard text for statistics and data mining, and is now free:
[https://web.stanford.edu/~hastie/ElemStatLearn/](https://web.stanford.edu/~hastie/ElemStatLearn/)
Also Available [here](https://rads.stackoverflow.com/amzn/click/0387848576).
| null | CC BY-SA 3.0 | null | 2010-07-21T22:35:38.850 | 2017-10-15T12:25:14.017 | 2017-10-15T12:25:14.017 | 35740 | 36 | null |
471 | 2 | null | 363 | 22 | null | [Darrell Huff -- How to Lie with Statistics](http://rads.stackoverflow.com/amzn/click/0393310728)
| null | CC BY-SA 2.5 | null | 2010-07-21T22:57:58.260 | 2011-02-20T02:34:52.907 | 2011-02-20T02:34:52.907 | 159 | 168 | null |
472 | 2 | null | 170 | 11 | null | For getting into stochastic processes and SDEs, Tom Kurtz's [lecture notes](http://www.math.wisc.edu/~kurtz/m735.htm) are hard to beat. It starts with a decent review of probability and some convergence results, and then dives right into continuous time stochastic processes in fairly clear, comprehensible language. I... | null | CC BY-SA 2.5 | null | 2010-07-21T23:00:34.700 | 2010-07-21T23:00:34.700 | null | null | 61 | null |
473 | 2 | null | 369 | 3 | null | The traditional solution to this problem is to use the [vector representation](http://dx.doi.org/10.1137/S0036144598347035) for the news stories and then cluster the vectors. The vectors are arrays where each entry represents a word or word class. The value associated to each word will be the [tf-idf](http://en.wikip... | null | CC BY-SA 2.5 | null | 2010-07-22T02:37:18.820 | 2010-07-22T02:37:18.820 | null | null | 260 | null |
474 | 2 | null | 30 | 8 | null | For testing the numbers produced by random number generators the [Diehard tests](http://en.wikipedia.org/wiki/Diehard_tests) are a practical approach. But those tests seem kind of arbitrary and one is may be left wondering if more should be included or if there is any way to really check the randomness.
The best cand... | null | CC BY-SA 2.5 | null | 2010-07-22T03:21:18.913 | 2010-07-22T03:21:18.913 | null | null | 260 | null |
475 | 2 | null | 224 | 4 | null | There is also [Gephi](http://gephi.org/) for plotting social networks.
(p.s: Here is how to [connect it with R](http://www.r-bloggers.com/data-preparation-for-social-network-analysis-using-r-and-gephi/))
| null | CC BY-SA 2.5 | null | 2010-07-22T03:55:48.147 | 2010-07-22T03:55:48.147 | null | null | 253 | null |
476 | 2 | null | 359 | 8 | null | I won't give a definitive answer in terms of ranking the three. Build 95% CIs around your parameters based on each, and if they're radically different, then your first step should be to dig deeper. Transform your data (though the LR will be invariant), regularize your likelihood, etc. In a pinch though, I would prob... | null | CC BY-SA 2.5 | null | 2010-07-22T04:34:32.110 | 2010-07-22T04:34:32.110 | null | null | 251 | null |
477 | 2 | null | 223 | 1 | null | I assume your friend prefers something that's biostatistics oriented. Glantz's [Primer of Biostatistics](http://www.powells.com/biblio/62-9780071435093-1) is a small book, an easy and quick read, and tends to get rave reviews from a similar audience. If an online reference works, I like Gerard Dallal's [Handbook of S... | null | CC BY-SA 4.0 | null | 2010-07-22T04:58:50.427 | 2022-11-23T12:47:35.583 | 2022-11-23T12:47:35.583 | 362671 | 251 | null |
478 | 2 | null | 421 | 17 | null | I'm going to assume some basic statistics knowledge and recommend:
- The Statistical Sleuth (Ramsey, Schafer) which contain a good deal of mini case studies as they cover the basic statistical tools for data analysis.
- A First Course in Multivariate Statistics (Flury) which covers the essential statistics required... | null | CC BY-SA 3.0 | null | 2010-07-22T05:13:17.627 | 2012-08-16T01:32:09.280 | 2012-08-16T01:32:09.280 | 13280 | 251 | null |
479 | 2 | null | 459 | 10 | null | If it does not break your styleguide I would rather color the background of the plots red/(yellow/)green than just plotting a line. In my imagination this should make it pretty clear to a user that values are fine on green and to be checked on red. Just my 5¢.
| null | CC BY-SA 2.5 | null | 2010-07-22T07:28:42.960 | 2010-07-22T07:28:42.960 | null | null | 128 | null |
480 | 1 | 635 | null | 20 | 4413 | I am not an expert of random forest but I clearly understand that the key issue with random forest is the (random) tree generation. Can you explain me how the trees are generated? (i.e. What is the used distribution for tree generation?)
Thanks in advance !
| How does random forest generate the random forest | CC BY-SA 2.5 | null | 2010-07-22T08:58:36.800 | 2022-06-18T13:42:20.083 | 2010-07-26T16:57:59.560 | 217 | 223 | [
"machine-learning",
"r",
"algorithms",
"cart",
"random-forest"
] |
481 | 1 | 482 | null | 11 | 5413 | Another question about time series from me.
I have a dataset which gives daily records of violent incidents in a psychiatric hospital over three years. With the help from my previous question I have been fiddling with it and am a bit happier about it now.
The thing I have now is that the daily series is very noisy. It ... | Is it valid to aggregate a time series to make it look more meaningful? | CC BY-SA 2.5 | null | 2010-07-22T09:17:27.490 | 2010-07-23T08:15:23.430 | null | null | 199 | [
"time-series",
"forecasting"
] |
482 | 2 | null | 481 | 8 | null | This totally depends on your time series and what effect you want to discover/proof etc.
An important thing here is, what kind of periods do you have in your data. Make a spectrum of you data and see what frequencies are common in you data.
Anyway, you are not lying when you decide to display aggregated values. When yo... | null | CC BY-SA 2.5 | null | 2010-07-22T09:24:52.503 | 2010-07-22T09:24:52.503 | null | null | 190 | null |
483 | 2 | null | 480 | 19 | null | The main idea is the bagging procedure, not making trees random. In detail, each tree is built on a sample of objects drawn with replacement from the original set; thus each tree has some objects that it hasn't seen, which is what makes the whole ensemble more heterogeneous and thus better in generalizing.
Furthermore,... | null | CC BY-SA 4.0 | null | 2010-07-22T09:53:52.400 | 2022-06-18T13:42:20.083 | 2022-06-18T13:42:20.083 | 361019 | null | null |
485 | 1 | null | null | 57 | 9120 | A question previously sought recommendations for [textbooks on mathematical statistics](https://stats.stackexchange.com/questions/414/intro-to-statistics-for-mathematicians)
Does anyone know of any good online video lectures on mathematical statistics?
The closest that I've found are:
- Machine Learning
- Econometri... | Mathematical Statistics Videos | CC BY-SA 2.5 | null | 2010-07-22T10:08:10.067 | 2022-12-31T07:32:40.610 | 2017-04-13T12:58:32.177 | -1 | 183 | [
"mathematical-statistics",
"references"
] |
486 | 1 | 720 | null | 46 | 91129 | I have calculated AIC and AICc to compare two general linear mixed models; The AICs are positive with model 1 having a lower AIC than model 2. However, the values for AICc are both negative (model 1 is still < model 2). Is it valid to use and compare negative AICc values?
| Negative values for AICc (corrected Akaike Information Criterion) | CC BY-SA 2.5 | null | 2010-07-22T10:11:15.210 | 2016-09-01T12:56:57.487 | 2011-01-30T18:09:40.193 | 449 | 266 | [
"mixed-model",
"model-selection",
"aic"
] |
487 | 2 | null | 363 | 14 | null | Not a book, but I recently discovered an article by Jacob Cohen in American Psychologist entitled "Things I have learned (so far)." It's available as a pdf [here](https://pdfs.semanticscholar.org/fa77/0a7fb7c45a59abbc4c2bc7d174fa51e5d946.pdf).
| null | CC BY-SA 4.0 | null | 2010-07-22T10:15:28.313 | 2019-02-07T13:12:24.100 | 2019-02-07T13:12:24.100 | 77222 | 266 | null |
488 | 2 | null | 421 | 14 | null | A lot of Social Science / Psychology students with minimal mathematical background like Andy Field's book: [Discovering Statistics Using SPSS](http://rads.stackoverflow.com/amzn/click/0761944524). He also has a website that shares a [lot of material](http://www.statisticshell.com/html/woodofsuicides.html).
| null | CC BY-SA 3.0 | null | 2010-07-22T10:16:18.263 | 2013-09-28T00:27:23.313 | 2013-09-28T00:27:23.313 | 30807 | 183 | null |
489 | 2 | null | 396 | 3 | null | It also depends on where you wan't to publish your plots. You'll save yourself a lot of trouble by consulting the guide for authors before making any plots for a journal.
Also save the plots in a format that is easy to modify or save the code you have used to create them. Chances are that you need to make corrections.... | null | CC BY-SA 2.5 | null | 2010-07-22T11:05:55.197 | 2010-07-22T11:05:55.197 | null | null | 214 | null |
490 | 1 | 606 | null | 30 | 17314 | What are the variable/feature selection that you prefer for binary classification when there are many more variables/feature than observations in the learning set? The aim here is to discuss what is the feature selection procedure that reduces the best the classification error.
We can fix notations for consistency: f... | Variable selection procedure for binary classification | CC BY-SA 3.0 | null | 2010-07-22T11:10:29.417 | 2016-04-05T12:33:34.737 | 2017-04-13T12:44:33.237 | -1 | 223 | [
"machine-learning",
"classification",
"multiple-comparisons",
"multivariate-analysis",
"feature-selection"
] |
491 | 2 | null | 421 | 3 | null | I recently found [Even You Can Learn Statistics](http://rads.stackoverflow.com/amzn/click/0131467573) to be pretty useful.
| null | CC BY-SA 2.5 | null | 2010-07-22T11:19:10.587 | 2010-07-22T11:19:10.587 | null | null | 268 | null |
492 | 1 | null | null | 11 | 1214 | I am proposing to try and find a trend in some very noisy long term data. The data is basically weekly measurements of something which moved about 5mm over a period of about 8 months. The data is to 1mm accuracey and is very noisy regularly changing +/-1 or 2mm in a week. We only have the data to the nearest mm.
We pl... | Dubious use of signal processing principles to identify a trend | CC BY-SA 2.5 | null | 2010-07-22T11:31:16.777 | 2015-04-23T14:38:18.937 | 2012-06-07T20:31:39.863 | 919 | 210 | [
"time-series",
"data-mining",
"signal-processing",
"trend"
] |
493 | 2 | null | 170 | 7 | null | Statsoft's [Electronic Statistics Handbook](http://www.statsoft.com/textbook/) ('The only Internet Resource about Statistics Recommended by Encyclopedia Britannica') is worth checking out.
| null | CC BY-SA 2.5 | null | 2010-07-22T11:33:47.037 | 2010-07-22T11:33:47.037 | null | null | 268 | null |
494 | 2 | null | 486 | 14 | null | Generally, it is assumed that AIC (and so AICc) is defined up to adding a constant, so the fact if it is negative or positive is not meaningful at all. So the answer is yes, it is valid.
| null | CC BY-SA 2.5 | null | 2010-07-22T11:42:42.967 | 2010-07-22T20:16:08.967 | 2010-07-22T20:16:08.967 | null | null | null |
495 | 2 | null | 485 | 6 | null | There is one called [Math and probability for life sciences](http://www.academicearth.org/courses/math-and-proability-for-life-sciences), but I haven't followed it so I can't tell you if its good or not.
| null | CC BY-SA 2.5 | null | 2010-07-22T11:43:42.560 | 2010-07-22T11:43:42.560 | null | null | 214 | null |
496 | 2 | null | 492 | 7 | null | I think you can get some distortion on the pasting point as not all the underlying waves will connect very well.
I would suggest using a Hilbert Huang transform for this. Just do the split into intrinsic mode functions and see what is left over as residue when calculating them.
| null | CC BY-SA 2.5 | null | 2010-07-22T11:44:13.230 | 2010-07-22T11:44:13.230 | null | null | 190 | null |
497 | 2 | null | 490 | 4 | null | Greedy forward selection.
The steps for this method are:
- Make sure you have a train and validation set
- Repeat the following
Train a classifier with each single feature separately that is not selected yet and with all the previously selected features
If the result improves, add the best performing feature, else s... | null | CC BY-SA 2.5 | null | 2010-07-22T11:53:51.010 | 2010-07-22T11:53:51.010 | null | null | 190 | null |
498 | 1 | null | null | 2 | 14808 | Sometimes, I just want to do a copy & paste from the output window in SAS. I can highlight text with a mouse-drag, but only SOMETIMES does that get copied to the clipboard. It doesn't matter if I use "CTRL-C" or right click -> copy, or edit -> copy
Any other SAS users experience this, and do you know a workaround/optio... | In SAS, how do you copy & paste from the output window? | CC BY-SA 3.0 | null | 2010-07-22T11:58:21.923 | 2015-07-08T21:53:12.013 | 2015-07-08T21:53:12.013 | 28666 | 62 | [
"sas"
] |
499 | 1 | 3728 | null | 20 | 685 | I've heard that when many regression model specifications (say, in OLS) are considered as possibilities for a dataset, this causes multiple comparison problems and the p-values and confidence intervals are no longer reliable. One extreme example of this is stepwise regression.
When can I use the data itself to help spe... | When can you use data-based criteria to specify a regression model? | CC BY-SA 2.5 | null | 2010-07-22T12:06:28.817 | 2010-10-19T01:50:06.413 | 2010-07-22T13:26:10.600 | 267 | 267 | [
"regression",
"frequentist",
"multiple-comparisons"
] |
500 | 2 | null | 499 | 2 | null | If I understand your question right, than the answer to your problem is to correct the p-values accordingly to the number of hypothesis.
For example Holm-Bonferoni corrections, where you sort the hypothesis (= your different models) by their p-value and reject those with a p samller than (desired p-value / index).
More... | null | CC BY-SA 2.5 | null | 2010-07-22T12:16:29.217 | 2010-07-22T12:16:29.217 | null | null | 190 | null |
501 | 2 | null | 490 | 2 | null | Backward elimination.
Start with the full set, then iteratively train the classifier on the remaining features and remove the feature with the smallest importance, stop when the classifier error rapidly increases/becomes unacceptable high.
Importance can be even obtained by removing iteratively each feature and check t... | null | CC BY-SA 2.5 | null | 2010-07-22T12:17:20.900 | 2010-07-22T13:05:25.687 | 2010-07-22T13:05:25.687 | 223 | null | null |
502 | 2 | null | 485 | 5 | null | I do not know at what level you want the videos to be but I have heard good things about Khan's Academy: [http://www.khanacademy.org/#Statistics](http://www.khanacademy.org/#Statistics)
| null | CC BY-SA 2.5 | null | 2010-07-22T12:25:42.333 | 2010-07-22T12:25:42.333 | null | null | null | null |
503 | 2 | null | 498 | 2 | null | I have been using SAS a long time and have never had an issue with highlighting results from the output window.
However since you are having an issue... there are alarge number of solutions!
Perhaps the most i like... and probably a good habit to get into is to output your results into datasets... or into excel spread ... | null | CC BY-SA 2.5 | null | 2010-07-22T12:25:48.810 | 2010-07-22T12:25:48.810 | null | null | 256 | null |
504 | 2 | null | 485 | 5 | null | Many of the Berkeley introductory statistics courses are available online (and on iTunes). Here's an example: [Stats 2](http://webcast.berkeley.edu/course_details.php?seriesid=1906978493). You can [find more here](http://www.google.com/search?hl=en&rlz=1C1CHMP_en-USUS292US307&q=statistics+video+site%3awebcast.berkele... | null | CC BY-SA 2.5 | null | 2010-07-22T12:33:49.683 | 2010-07-22T12:33:49.683 | null | null | 5 | null |
505 | 2 | null | 490 | 7 | null | Metropolis scanning / MCMC
- Select few features randomly for a
start, train classifier only on them
and obtain the error.
- Make some
random change to this working set --
either remove one feature, add
another at random or replace some
feature with one not being currently
used.
- Train new classifier and get
its e... | null | CC BY-SA 2.5 | null | 2010-07-22T12:42:13.893 | 2010-07-22T12:42:13.893 | null | null | null | null |
506 | 2 | null | 287 | 30 | null | Both MOM and GMM are very general methods for estimating parameters of statistical models. GMM is - as the name suggests - a generalisation of MOM. It was developed by Lars Peter Hansen and first published in Econometrica [1]. As there are numerous textbooks on the subject (e.g. [2]) I presume you want a non-technical ... | null | CC BY-SA 4.0 | null | 2010-07-22T13:10:57.267 | 2021-02-26T17:25:32.740 | 2021-02-26T17:25:32.740 | 53690 | 215 | null |
507 | 1 | 560 | null | 31 | 23717 | What is your preferred method of checking for convergence when using Markov chain Monte Carlo for Bayesian inference, and why?
| What is the best method for checking convergence in MCMC? | CC BY-SA 2.5 | null | 2010-07-22T13:40:30.237 | 2017-12-07T20:01:56.177 | null | null | 215 | [
"bayesian",
"markov-chain-montecarlo"
] |
508 | 2 | null | 396 | 2 | null | I would add that the choice of plot should reflect the type of statistical test used to analyse the data. In other words, whatever characteristics of the data were used for analysis should be shown visually - so you would show means and standard errors if you used a t-test but boxplots if you used a Mann-Whitney test.... | null | CC BY-SA 2.5 | null | 2010-07-22T13:41:53.637 | 2010-07-22T13:41:53.637 | null | null | 266 | null |
509 | 2 | null | 507 | 2 | null | I like to do trace plots primarily and sometimes I use the Gelman-Rubin convergence diagnostic.
| null | CC BY-SA 2.5 | null | 2010-07-22T13:43:18.233 | 2010-07-22T13:43:18.233 | null | null | null | null |
510 | 2 | null | 423 | 65 | null | More about design and power than analysis, but I like this one
| null | CC BY-SA 2.5 | null | 2010-07-22T13:49:37.283 | 2010-07-22T13:49:37.283 | 2017-03-09T17:30:36.233 | -1 | 266 | null |
511 | 2 | null | 423 | 38 | null | From [xkcd](http://xkcd.com/701/):
If some people who really believe that everything should be scientifically tested would actually walk their talk than they this comic might even sh... | null | CC BY-SA 2.5 | null | 2010-07-22T14:32:20.363 | 2010-07-22T14:32:20.363 | 2017-03-09T17:30:36.247 | -1 | 3807 | null |
512 | 2 | null | 492 | 8 | null | If you want to filter the long term trend out using signal processing, why not just use a low-pass?
The simplest thing I can think of would be an exponential moving average.
| null | CC BY-SA 2.5 | null | 2010-07-22T14:52:54.510 | 2010-07-22T14:52:54.510 | null | null | 33 | null |
513 | 2 | null | 276 | 3 | null | I like to use resampling: I repeat whatever method I used with a subsample of the data (say 80% or even 50% of the total). By doing this with many different subsamples, I get a feel for how robust the estimates are. For many estimation procedures this can be made into a real (meaning publishable) estimate of your err... | null | CC BY-SA 2.5 | null | 2010-07-22T15:22:20.527 | 2010-07-22T15:22:20.527 | null | null | 260 | null |
514 | 2 | null | 26 | 3 | null | Here's how I would answer this question using a diagram.
Let's say we weigh 30 cats and calculate the mean weight. Then we produce a scatter plot, with weight on the y axis and cat identity on the x axis. The mean weight can be drawn in as a horizontal line. We can then draw in vertical lines which connect each da... | null | CC BY-SA 2.5 | null | 2010-07-22T15:36:53.510 | 2010-07-22T15:36:53.510 | null | null | 266 | null |
515 | 2 | null | 155 | 10 | null | 1) A good demonstration of how "random" needs to be defined in order to work out probability of certain events:
What is the chance that a random line drawn across a circle will be longer than the radius?
The question totally depends how you draw your line. Possibilities which you can describe in a real-world way for a ... | null | CC BY-SA 3.0 | null | 2010-07-22T15:49:54.270 | 2013-10-23T15:29:05.390 | 2013-10-23T15:29:05.390 | 17230 | 270 | null |
516 | 2 | null | 486 | 6 | null | Yes it's valid to compare negative AICc values, in the same way as you would negative AIC values. The correction factor in the AICc can become large with small sample size and relatively large number of parameters, and penalize heavier than the AIC. So positive AIC values can correspond to negative AICc values.
| null | CC BY-SA 2.5 | null | 2010-07-22T16:00:44.953 | 2010-07-22T16:00:44.953 | null | null | 251 | null |
517 | 1 | 522 | null | 29 | 30264 | In the context of machine learning, what is the difference between
- unsupervised learning
- supervised learning and
- semi-supervised learning?
And what are some of the main algorithmic approaches to look at?
| Unsupervised, supervised and semi-supervised learning | CC BY-SA 4.0 | null | 2010-07-22T16:21:06.090 | 2019-05-11T14:47:37.750 | 2019-03-20T16:30:26.923 | 128677 | 68 | [
"machine-learning",
"unsupervised-learning",
"supervised-learning",
"semi-supervised-learning"
] |
518 | 2 | null | 183 | 3 | null | Try [R](http://www.r-project.org/). [Here](http://cran.at.r-project.org/web/views/Cluster.html) you have a list of clustering packages available.
| null | CC BY-SA 2.5 | null | 2010-07-22T16:24:10.190 | 2010-07-22T16:24:10.190 | null | null | null | null |
519 | 2 | null | 36 | 5 | null | I read (a long time ago) of an interesting example about a decline in birth rates (or fertility rates if you prefer that measure) especially in the US, starting in the early 1960's, as nuclear weapons testing was at an all-time high (in 1961 the biggest nuclear bomb ever detonated was tested in the USSR). Rates contin... | null | CC BY-SA 2.5 | null | 2010-07-22T16:32:57.967 | 2010-07-22T16:32:57.967 | null | null | 270 | null |
520 | 2 | null | 183 | 2 | null | Python will give you all the flexibility you need. With the NumPy and [SciPy cluster module](http://docs.scipy.org/doc/scipy/reference/cluster.html) you have the tools you need, and the datatypes of NumPy give you a good insight in how much memory you will use.
| null | CC BY-SA 2.5 | null | 2010-07-22T16:33:43.240 | 2010-07-22T16:33:43.240 | null | null | 190 | null |
521 | 2 | null | 517 | 14 | null | Unsupervised Learning
Unsupervised learning is when you have no labeled data available for training. Examples of this are often clustering methods.
Supervised Learning
In this case your training data exists out of labeled data. The problem you solve here is often predicting the labels for data points without label.
Sem... | null | CC BY-SA 2.5 | null | 2010-07-22T16:39:05.870 | 2010-07-22T16:39:05.870 | null | null | 190 | null |
522 | 2 | null | 517 | 24 | null | Generally, the problems of machine learning may be considered variations on function estimation for classification, prediction or modeling.
In supervised learning one is furnished with input ($x_1$, $x_2$, ...,) and output ($y_1$, $y_2$, ...,) and are challenged with finding a function that approximates this behavior i... | null | CC BY-SA 4.0 | null | 2010-07-22T18:03:43.437 | 2019-03-20T16:29:31.593 | 2019-03-20T16:29:31.593 | 128677 | 39 | null |
523 | 2 | null | 517 | 8 | null | I don't think that supervised/unsupervised is the best way to think about it. For basic data mining, it's better to think about what you are trying to do. There are four main tasks:
- prediction. if you are predicting a real number, it is called regression. if you are predicting a whole number or class, it is called c... | null | CC BY-SA 2.5 | null | 2010-07-22T18:16:08.797 | 2010-08-13T17:59:07.270 | 2010-08-13T17:59:07.270 | 74 | 74 | null |
524 | 1 | 525 | null | 12 | 830 | Debugging MCMC programs is notoriously difficult. The difficulty arises because of several issues some of which are:
(a) Cyclic nature of the algorithm
We iteratively draw parameters conditional on all other parameters. Thus, if a implementation is not working properly it is difficult to isolate the bug as the issue ca... | Is there a standard technique to debug MCMC programs? | CC BY-SA 2.5 | null | 2010-07-22T18:25:54.250 | 2018-08-27T16:10:58.463 | 2018-08-27T16:10:58.463 | 11887 | null | [
"markov-chain-montecarlo"
] |
525 | 2 | null | 524 | 11 | null | Standard programming practice:
- when debugging run the simulation with fixed sources of randomness (i.e. same seed) so that any changes are due to code changes and not different random numbers.
- try your code on a model (or several models) where the answer IS known.
- adopt good programming habits so that you intr... | null | CC BY-SA 3.0 | null | 2010-07-22T18:33:47.900 | 2016-10-27T19:03:15.123 | 2016-10-27T19:03:15.123 | 123561 | 247 | null |
526 | 1 | 585 | null | 9 | 551 | As you know, there are two popular types of cross-validation, K-fold and random subsampling (as described in [Wikipedia](http://en.wikipedia.org/wiki/Cross-validation_%28statistics%29)). Nevertheless, I know that some researchers are making and publishing papers where something that is described as a K-fold CV is indee... | Does the cross validation implementation influence its results? | CC BY-SA 2.5 | null | 2010-07-22T19:17:41.870 | 2010-07-24T22:54:13.430 | null | null | null | [
"machine-learning",
"cross-validation"
] |
527 | 1 | 2834 | null | 12 | 12417 | I have two different analytical methods that can measure the concentration of a particular molecule in a matrix (for instance measure the amount of salt in water)
The two methods are different, and each has it's own error. What ways exist to show the two methods are equivalent (or not).
I'm thinking that plotting the ... | What ways are there to show two analytical methods are equivalent? | CC BY-SA 2.5 | null | 2010-07-22T21:15:52.347 | 2016-07-13T08:11:43.100 | 2016-07-13T08:11:43.100 | 1352 | 114 | [
"hypothesis-testing",
"measurement-error",
"method-comparison",
"bland-altman-plot"
] |
528 | 2 | null | 36 | 2 | null | Teaching "Correlation does not mean causation" doesn't really help anyone because at the end of the day all deductive arguments are based in part on correlation.
Human are very bad at learning not to do something.
The goal should rather be constructive: Always think about alternatives to your starting assumptions that... | null | CC BY-SA 2.5 | null | 2010-07-22T22:33:37.800 | 2010-07-22T22:33:37.800 | null | null | 3807 | null |
529 | 2 | null | 527 | 0 | null | Your use of the phrase 'analytical methods' is a bit confusing to me. I am going to assume that by 'analytical methods' you mean some specific model/estimation strategy.
Broadly, speaking there are two types of metrics you could use to choose between estimators.
In-sample Metrics
- Likelihood ratio / Wald test / Scor... | null | CC BY-SA 2.5 | null | 2010-07-22T22:38:05.597 | 2010-07-22T22:38:05.597 | null | null | null | null |
530 | 2 | null | 481 | 12 | null | It's very common in forecasting to aggregate data in order to increase the signal/noise ratio. There are several papers on the effect of temporal aggregation on forecast accuracy in economics, for example. What you're probably seeing in the daily data is a weak signal that is being swamped by noise, whereas the weekly... | null | CC BY-SA 2.5 | null | 2010-07-22T23:52:24.403 | 2010-07-22T23:52:24.403 | null | null | 159 | null |
531 | 2 | null | 499 | 4 | null | I don't think it is possible to do Bonferoni or similar corrections to adjust for variable selection in regression because all the tests and steps involved in model selection are not independent.
One approach is to formulate the model using one set of data, and do inference on a different set of data. This is done in f... | null | CC BY-SA 2.5 | null | 2010-07-23T00:04:48.980 | 2010-07-23T00:04:48.980 | null | null | 159 | null |
532 | 2 | null | 213 | 21 | null | I think Robin Girard's answer would work pretty well for 3 and possibly 4 dimensions, but the curse of dimensionality would prevent it working beyond that. However, his suggestion led me to a related approach which is to apply the cross-validated kernel density estimate to the first three principal component scores. Th... | null | CC BY-SA 2.5 | null | 2010-07-23T01:44:22.153 | 2010-07-23T01:44:22.153 | null | null | 159 | null |
533 | 2 | null | 155 | 8 | null | Along the lines of the mean as balance point, I like this view of the median as a balance point:
- A Pearl: a Balanced Median Necklace
| null | CC BY-SA 2.5 | null | 2010-07-23T01:48:56.683 | 2010-07-23T01:48:56.683 | null | null | 251 | null |
534 | 1 | 538 | null | 104 | 69075 | We all know the mantra "correlation does not imply causation" which is drummed into all first year statistics students. There are some nice examples [here](https://stats.stackexchange.com/questions/36/correlation-does-not-mean-causation) to illustrate the idea.
But sometimes correlation does imply causation. The follow... | Under what conditions does correlation imply causation? | CC BY-SA 2.5 | null | 2010-07-23T01:56:02.517 | 2020-11-16T13:48:14.220 | 2017-04-13T12:44:28.813 | -1 | 159 | [
"correlation",
"causality"
] |
535 | 2 | null | 534 | 3 | null | Almost surely in a well designed experiment. (Designed, of course, to elicit such a [connexion](http://18th.eserver.org/hume-enquiry.html#7).)
| null | CC BY-SA 2.5 | null | 2010-07-23T02:00:12.007 | 2010-07-23T02:06:23.333 | 2010-07-23T02:06:23.333 | 251 | 251 | null |
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