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856 | 1 | 1306 | null | 13 | 6485 | Does anyone know of a variation of Fisher's Exact Test which takes weights into account? For instance [sampling weights](http://www.measuredhs.com/help/Datasets/sampling_weights.htm).
So instead of the usual 2x2 cross table, every data point has a "mass" or "size" value weighing the point.
Example data:
```
A B weight
... | Fisher's Exact Test with weights? | CC BY-SA 2.5 | null | 2010-07-27T20:24:45.767 | 2011-04-24T08:04:05.637 | 2010-07-29T15:21:16.363 | 506 | 506 | [
"hypothesis-testing"
] |
857 | 2 | null | 775 | 6 | null | Operations Research began during wartime in the 1940s with scientists and others addressing problems in Radar operations, Anti-Submarine Warfare (ASW), and air operations. It is really a methodology to help decision makers choose a course of action by using an analytic framework that includes statistics, linear and non... | null | CC BY-SA 2.5 | null | 2010-07-27T20:25:16.327 | 2010-07-27T20:25:16.327 | null | null | 482 | null |
858 | 2 | null | 837 | 3 | null | I'm not sure why this doesn't work with `lrm`. However, R does Logistic Regression just fine with its own internal functions. See GLM. Here's your model, working...
```
summary(glm(am~1, data = mtcars, family=binomial(link=logit)))
```
So, unless you need something that `lrm()` from design provides, then use GLM wi... | null | CC BY-SA 3.0 | null | 2010-07-27T20:33:48.787 | 2013-08-09T00:48:47.660 | 2013-08-09T00:48:47.660 | 7290 | 485 | null |
859 | 1 | 867 | null | 12 | 5991 | Sorry for the verbose background to this question:
Occasionally in investigations of animal behaviour, an experimenter is interested in the amount of time that a subject spends in different, pre-defined zones in a test apparatus. I've often seen this sort of data analyzed using ANOVA; however, I have never been entirel... | ANOVA with non-independent observations | CC BY-SA 2.5 | null | 2010-07-27T21:07:20.127 | 2014-05-21T17:36:11.060 | 2010-12-21T17:06:54.740 | 930 | 445 | [
"anova"
] |
860 | 2 | null | 834 | 7 | null | Let $f$ be your true distribution, and $g$ the family from which you are trying to fit your data. Then $\theta$, the maximum likelihood estimator of parameters of $g$, is a random variable. You could formulate model selection as finding the distribution family $g$ that minimizes the expected KL divergence between $f$ a... | null | CC BY-SA 2.5 | null | 2010-07-27T21:51:43.650 | 2010-11-18T00:36:44.833 | 2010-11-18T00:36:44.833 | 159 | 511 | null |
861 | 2 | null | 743 | 3 | null | There is a free book on Geostatistical Mapping with R [here](http://spatial-analyst.net/book/) it might help your problem.
| null | CC BY-SA 2.5 | null | 2010-07-27T22:33:05.287 | 2010-07-27T22:33:05.287 | null | null | 481 | null |
862 | 2 | null | 798 | 146 | null | The [Freedman-Diaconis](https://en.wikipedia.org/wiki/Freedman%E2%80%93Diaconis_rule) rule is very robust and works well in practice. The bin-width is set to $h=2\times\text{IQR}\times n^{-1/3}$. So the number of bins is $(\max-\min)/h$, where $n$ is the number of observations, max is the maximum value and min is the m... | null | CC BY-SA 4.0 | null | 2010-07-28T00:23:22.107 | 2019-01-31T23:55:44.507 | 2019-01-31T23:55:44.507 | 159 | 159 | null |
863 | 2 | null | 859 | 5 | null | Mike,
I agree that an ANOVA based on total time probably isn't the correct approach here. Further, I'm not convinced that Chi Sqaure solves your problem. Chi square will respect the idea that you can't be in two locations at the same time, but it doesn't address the problem that there are likely dependencies between ... | null | CC BY-SA 2.5 | null | 2010-07-28T00:29:41.487 | 2010-07-28T00:29:41.487 | null | null | 196 | null |
864 | 2 | null | 859 | 3 | null | I am going to suggest an answer that is very different from that of a traditional ANOVA. Let T be the total time that is available for an animal to spend in all the zones. You could define T as the total amount of waking time or some such. Suppose that you have J zones. Then by definition you have:
Sum T_j = T
You coul... | null | CC BY-SA 2.5 | null | 2010-07-28T01:00:22.877 | 2010-07-28T01:00:22.877 | null | null | null | null |
865 | 2 | null | 225 | 1 | null | Just to expand on Rob's answer a bit, suppose that we want to know the cumulative distribution function (CDF) of the highest value of $N$ independent draws from a standard normal distribution, $X_1, ..., X_N$. Call this highest value $Y_1$, the first order statistic. Then the CDF is:
$$ \begin{align*}P(Y_1 < x) &= P(\m... | null | CC BY-SA 3.0 | null | 2010-07-28T01:06:56.963 | 2012-04-01T04:18:55.447 | 2012-04-01T04:18:55.447 | 401 | 401 | null |
866 | 1 | 876 | null | 206 | 165951 | Say I want to estimate a large number of parameters, and I want to penalize some of them because I believe they should have little effect compared to the others. How do I decide what penalization scheme to use? When is ridge regression more appropriate? When should I use lasso?
| When should I use lasso vs ridge? | CC BY-SA 2.5 | null | 2010-07-28T01:10:18.423 | 2017-10-11T16:20:05.347 | 2010-08-09T12:25:13.010 | 159 | 455 | [
"regression",
"lasso",
"ridge-regression"
] |
867 | 2 | null | 859 | 3 | null | (Caveat Emptor: I'm not an expert in this area)
If you just want to talk about differences in time spent per location, then submitting the "time-per-location" data as counts in a multinomial mixed model (see the MCMCglmm package for R), using subject as a random effect, should do the trick.
If you want to talk about d... | null | CC BY-SA 2.5 | null | 2010-07-28T01:17:57.410 | 2010-07-28T01:17:57.410 | null | null | 364 | null |
868 | 1 | 917 | null | 4 | 2824 | I created a quick fun Excel Spreadsheet tonight to try and predict which video games I'll enjoy if I buy them. I'm wondering if this quick example makes sense from a Logistic Regression perspective and if I am computing all of the values correctly.
Unfortunately, if I did everything correctly I doubt I have much to loo... | Training a Logistic Regression Model | CC BY-SA 2.5 | null | 2010-07-28T03:15:34.473 | 2011-01-07T01:55:24.827 | null | null | 9426 | [
"logit",
"logistic"
] |
869 | 2 | null | 868 | 2 | null | Usually in logistic regression you'd want "successes" to be 1 and "failures" to be 0, but so long as you are consistent in how you enter your data and interpret it, the coefficients don't really care.
| null | CC BY-SA 2.5 | null | 2010-07-28T03:49:27.933 | 2010-07-28T03:49:27.933 | null | null | 196 | null |
870 | 1 | 956 | null | 28 | 32628 | Given a list of p-values generated from independent tests, sorted in ascending order, one can use the [Benjamini-Hochberg procedure](http://www.math.tau.ac.il/%7Eybenja/MyPapers/benjamini_hochberg1995.pdf) for [multiple testing correction](https://en.wikipedia.org/wiki/False_discovery_rate#Independent_tests). For each ... | Multiple hypothesis testing correction with Benjamini-Hochberg, p-values or q-values? | CC BY-SA 4.0 | null | 2010-07-28T03:54:56.447 | 2022-06-23T20:57:07.927 | 2022-06-23T20:57:07.927 | 79696 | 520 | [
"hypothesis-testing"
] |
871 | 1 | 875 | null | 54 | 41056 | I realize this is pedantic and trite, but as a researcher in a field outside of statistics, with limited formal education in statistics, I always wonder if I'm writing "p-value" correctly. Specifically:
- Is the "p" supposed to be capitalized?
- Is the "p" supposed to be italicized? (Or in mathematical font, in TeX?)... | Correct spelling (capitalization, italicization, hyphenation) of "p-value"? | CC BY-SA 3.0 | null | 2010-07-28T04:08:23.973 | 2018-11-17T09:19:45.610 | 2016-12-09T16:38:27.097 | 28666 | 520 | [
"hypothesis-testing",
"p-value",
"terminology"
] |
872 | 2 | null | 871 | 8 | null | This seems to be a style issue with different journals and publishers adopting different conventions (or allowing a mixed muddle of styles depending on authors' preferences). My own preference, for what it's worth, is p-value, hyphenated with no italics and no capitalization.
| null | CC BY-SA 2.5 | null | 2010-07-28T04:21:06.723 | 2010-07-28T04:21:06.723 | null | null | 159 | null |
873 | 2 | null | 871 | 5 | null | The [ASA House Style](http://www.amstat.org/publications/chance/assets/style.pdf) seems to recommend italicizing the p with hyphen: p-value. A google scholar search shows [varied spellings](http://scholar.google.com/scholar?q=p+value&hl=en&btnG=Search&as_sdt=80001&as_sdtp=on).
| null | CC BY-SA 2.5 | null | 2010-07-28T04:24:05.240 | 2010-07-28T04:24:05.240 | null | null | 251 | null |
874 | 2 | null | 866 | 53 | null | Ridge or lasso are forms of regularized linear regressions. The regularization can also be interpreted as prior in a maximum a posteriori estimation method. Under this interpretation, the ridge and the lasso make different assumptions on the class of linear transformation they infer to relate input and output data. ... | null | CC BY-SA 2.5 | null | 2010-07-28T04:26:17.297 | 2010-07-28T04:26:17.297 | null | null | 260 | null |
875 | 2 | null | 871 | 37 | null | There do not appear to be "standards". For example:
- The Nature style guide refers to "P value"
- This APA style guide refers to "p value"
- The Blood style guide says:
Capitalize and italicize the P that introduces a P value
Italicize the p that represents the Spearman rank correlation test
- Wikipedia uses "... | null | CC BY-SA 3.0 | null | 2010-07-28T04:29:37.107 | 2016-12-09T14:43:12.957 | 2016-12-09T14:43:12.957 | 28666 | 163 | null |
876 | 2 | null | 866 | 128 | null | Keep in mind that ridge regression can't zero out coefficients; thus, you either end up including all the coefficients in the model, or none of them. In contrast, the LASSO does both parameter shrinkage and variable selection automatically. If some of your covariates are highly correlated, you may want to look at the E... | null | CC BY-SA 3.0 | null | 2010-07-28T05:55:31.407 | 2013-07-26T13:52:42.580 | 2013-07-26T13:52:42.580 | 17230 | 530 | null |
877 | 1 | null | null | 3 | 1116 | Has anyone gone through some papers using Vector Error Correction Models in causality applications with more than one cointegration vectors, say two. I guess there will be more than one ECM terms. How to assess the endogeneity of the left hand variables if t-stats on different ECM coefficients yield different (conflic... | Time Series Econometrics: VECM with multiple cointegration vectors | CC BY-SA 2.5 | null | 2010-07-28T06:31:36.857 | 2010-07-28T06:31:36.857 | null | null | 531 | [
"econometrics"
] |
878 | 2 | null | 726 | 69 | null | >
Absence of evidence is not evidence of absence.
–[Martin Rees](https://en.wikiquote.org/wiki/Martin_Rees) ([Wikipedia](https://en.wikipedia.org/wiki/Evidence_of_absence))
| null | CC BY-SA 4.0 | null | 2010-07-28T06:49:12.123 | 2019-07-16T22:06:22.707 | 2019-07-16T22:06:22.707 | 143653 | null | null |
879 | 2 | null | 798 | 12 | null | Maybe the paper "[Variations on the histogram](http://pubs.research.avayalabs.com/pdfs/ALR-2007-003-paper.pdf)" by Denby and Mallows will be of interest:
>
This new display which we term "dhist" (for diagonally-cut histogram) preserves the desirable features of both the equal-width hist and the equal-area hist. It wil... | null | CC BY-SA 2.5 | null | 2010-07-28T07:23:22.887 | 2010-07-28T07:23:22.887 | null | null | 251 | null |
880 | 1 | null | null | 9 | 1154 | My question is about cross validation when there are many more variables than observations. To fix ideas, I propose to restrict to the classification framework in very high dimension (more features than observation).
Problem: Assume that for each variable $i=1,\dots,p$ you have a measure of importance $T[i]$ than exact... | Cross validation in very high dimension (to select the number of used variables in very high dimensional classification) | CC BY-SA 2.5 | null | 2010-07-28T08:15:40.827 | 2019-08-02T13:35:07.420 | 2010-09-02T07:13:57.967 | 223 | 223 | [
"machine-learning",
"classification",
"cross-validation"
] |
881 | 1 | 1189 | null | 6 | 1483 | Here's something I've wondered about for a while, but haven't been able to discover the correct terminology. Say you have a relatively complicated density function that you suspect might have a close approximation as a sum of (properly weighted) simpler density functions. Have such things been studied? I'm particularly... | Series expansion of a density function | CC BY-SA 2.5 | null | 2010-07-28T08:15:51.733 | 2011-03-28T08:58:47.087 | 2011-03-28T08:58:47.087 | null | 34 | [
"probability",
"mixture-distribution",
"density-function"
] |
882 | 2 | null | 881 | 4 | null | Histogram density estimator is estimating the density with a sum of piecewise functions (density of a uniform).
KDE is using a sum of smooth function (gaussian is an example) (as long as they are positive they can be transformed into a density by normalization)
The use of "mixture" in statistic is about convex combin... | null | CC BY-SA 2.5 | null | 2010-07-28T08:21:47.367 | 2010-08-03T19:20:24.017 | 2010-08-03T19:20:24.017 | 223 | 223 | null |
883 | 2 | null | 881 | 3 | null | You can do this with mixture modeling. There are a number of R packages on CRAN for doing this. Search for "mixture" at [http://cran.r-project.org/web/packages/](http://cran.r-project.org/web/packages/)
| null | CC BY-SA 2.5 | null | 2010-07-28T09:09:51.180 | 2010-07-28T09:09:51.180 | null | null | 159 | null |
884 | 1 | null | null | 28 | 1832 | >
Possible Duplicate:
How to understand degrees of freedom?
I was at a talk a few months back where the speaker used the term 'degrees of freedom'. She briefly said something along the lines of it meaning the number of values used to form a statistic that are free to vary.
What does this mean? I'm specifically look... | What are "degrees of freedom"? | CC BY-SA 2.5 | null | 2010-07-28T09:54:14.730 | 2012-08-07T09:37:08.443 | 2017-04-13T12:44:25.243 | -1 | 541 | [
"degrees-of-freedom"
] |
886 | 1 | 934 | null | 20 | 16503 | The 'fundamental' idea of statistics for estimating parameters is [maximum likelihood](http://en.wikipedia.org/wiki/Maximum_likelihood). I am wondering what is the corresponding idea in machine learning.
Qn 1. Would it be fair to say that the 'fundamental' idea in machine learning for estimating parameters is: 'Loss Fu... | What is the 'fundamental' idea of machine learning for estimating parameters? | CC BY-SA 2.5 | null | 2010-07-28T11:31:59.857 | 2017-08-29T15:26:29.920 | 2017-04-08T15:37:35.440 | 11887 | null | [
"machine-learning",
"maximum-likelihood",
"loss-functions",
"pac-learning"
] |
887 | 1 | null | null | 5 | 930 | Suppose there is a very big (infinite?) population of normally distributed values with unknown mean and variance.
Suppose also that we have a sample, S, of n values from the entire population. We can calculate mean and standard deviation for this sample (we use n-1 for stdev calculation).
The first and most important q... | Basic question regarding variance and stdev of a sample | CC BY-SA 3.0 | null | 2010-07-28T12:02:21.063 | 2017-12-31T10:52:59.010 | 2017-12-31T10:52:59.010 | 128677 | 213 | [
"standard-deviation",
"variance",
"normality-assumption",
"sample",
"unbiased-estimator"
] |
889 | 2 | null | 887 | 1 | null | My first answer was full of errors. Here is a corrected version:
The correct way to test is as follows:
z = (mean(S) - mu) / (stdev(S) / sqrt(n) )
See: [Student's t-test](http://en.wikipedia.org/wiki/Student%27s_t-test#Independent_one-sample_t-test)
Note the following:
- The sample size is accounted for when you divid... | null | CC BY-SA 2.5 | null | 2010-07-28T12:12:22.993 | 2010-07-28T12:20:09.950 | 2010-07-28T12:20:09.950 | null | null | null |
890 | 1 | null | null | 2 | 1136 | I am struggling a little bit at the moment with a question related to logistic regression. I have a model that predicts the occurrence of animal based on land cover with reference to forest. I am not grasping the concept of a reference class and struggle to extrapolate the model onto a new area. Any explanations or gui... | Reference category and prediction | CC BY-SA 3.0 | null | 2010-07-28T12:13:03.647 | 2012-10-27T22:09:44.950 | 2012-10-27T22:09:44.950 | null | null | [
"logistic"
] |
893 | 2 | null | 16921 | 23 | null | I really like first sentence from
[The Little Handbook of Statistical Practice. Degrees of Freedom Chapter](http://www.jerrydallal.com/LHSP/dof.htm)
>
One of the questions an instrutor
dreads most from a mathematically
unsophisticated audience is, "What
exactly is degrees of freedom?"
I think you can get real... | null | CC BY-SA 2.5 | null | 2010-07-28T12:48:14.233 | 2010-07-28T12:48:14.233 | null | null | 236 | null |
894 | 2 | null | 16921 | 90 | null | Or simply: the number of elements in a numerical array that you're allowed to change so that the value of the statistic remains unchanged.
```
# for instance if:
x + y + z = 10
```
you can change, for instance, x and y at random, but you cannot change z (you can, but not at random, therefore you're not free to change ... | null | CC BY-SA 2.5 | null | 2010-07-28T12:49:31.780 | 2010-07-28T17:34:31.507 | 2010-07-28T17:34:31.507 | 1356 | 1356 | null |
895 | 2 | null | 887 | 3 | null | I'm finding it rather tricky to see what you are asking:
- If you want to know whether the Var(S) is different from the population variance, then see this previous answer.
- If you want to determine whether the mean(S) and the mean(X) are the same, then look at Independent two-sample t-tests.
- If you want to test w... | null | CC BY-SA 2.5 | null | 2010-07-28T12:50:26.427 | 2010-07-28T12:50:26.427 | 2017-04-13T12:44:36.923 | -1 | 8 | null |
897 | 1 | 905 | null | 55 | 70748 | What is the difference between offline and [online learning](http://en.wikipedia.org/wiki/Online_machine_learning)? Is it just a matter of learning over the entire dataset (offline) vs. learning incrementally (one instance at a time)? What are examples of algorithms used in both?
| Online vs offline learning? | CC BY-SA 2.5 | null | 2010-07-28T13:32:32.843 | 2019-03-27T21:41:25.717 | 2018-11-05T11:38:08.473 | 11887 | 284 | [
"machine-learning",
"online-algorithms"
] |
898 | 1 | 918 | null | 7 | 2791 | I am interested in tools/techniques that can be used for analysis of [streaming data in "real-time"](http://en.wikipedia.org/wiki/Real-time_data)*, where latency is an issue. The most common example of this is probably price data from a financial market, although it also occurs in other fields (e.g. finding trends on ... | Modeling of real-time streaming data? | CC BY-SA 2.5 | null | 2010-07-28T13:49:07.733 | 2010-11-11T05:30:32.227 | null | null | 5 | [
"modeling",
"software",
"real-time"
] |
899 | 1 | null | null | 14 | 4672 | I'm trying to separate two groups of values from a single data set. I can assume that one of the populations is normally distributed and is at least half the size of the sample. The values of the second one are both lower or higher than the values from the first one (distribution is unknown). What I'm trying to do is t... | Separating two populations from the sample | CC BY-SA 3.0 | null | 2010-07-28T13:53:18.503 | 2013-03-17T16:07:09.307 | 2012-10-27T20:15:59.537 | 686 | 219 | [
"dataset",
"outliers",
"expectation-maximization"
] |
900 | 2 | null | 898 | 1 | null | I am not sure how far this would be relevant to what you want to do but see the paper on adaptive question design called [FASTPACE](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.120.8664&rep=rep1&type=pdf). The goal of the algorithm is to ask the next question from a survey respondent based on his/her previo... | null | CC BY-SA 2.5 | null | 2010-07-28T13:57:09.400 | 2010-07-28T13:57:09.400 | null | null | null | null |
901 | 2 | null | 73 | 2 | null | 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
| null | CC BY-SA 2.5 | null | 2010-07-28T13:59:49.157 | 2010-07-28T13:59:49.157 | null | null | 11 | null |
902 | 2 | null | 898 | 2 | null | It is going to depend a lot on what exactly you are looking for, but start at [Data Streams: Algorithms and Application by Muthukrishnan ](http://www.cs.rutgers.edu/~muthu/stream-1-1.ps).
There are many others that can be found by googling "data stream algorithms", or following the references in the paper.
| null | CC BY-SA 2.5 | null | 2010-07-28T14:01:46.063 | 2010-07-28T16:49:31.297 | 2010-07-28T16:49:31.297 | 247 | 247 | null |
903 | 2 | null | 485 | 3 | null | There is a series of Google Tech Talk videos called [Stats 202 - Statistical Aspects of Data Mining](http://video.google.com/videosearch?q=mease+stats+202&sitesearch=#)
| null | CC BY-SA 2.5 | null | 2010-07-28T14:06:35.367 | 2010-07-28T14:06:35.367 | null | null | 11 | null |
904 | 2 | null | 812 | 14 | null | Functional Data often involves different question. I've been reading Functional Data Analysis, Ramsey and Silverman, and they spend a lot of times discussing curve registration, warping functions, and estimating derivatives of curves. These tend to be very different questions than those asked by people interested in ... | null | CC BY-SA 2.5 | null | 2010-07-28T14:16:38.977 | 2010-07-28T14:16:38.977 | null | null | 549 | null |
905 | 2 | null | 897 | 51 | null | Online learning means that you are doing it as the data comes in. Offline means that you have a static dataset.
So, for online learning, you (typically) have more data, but you have time constraints. Another wrinkle that can affect online learning is that your concepts might change through time.
Let's say you want to b... | null | CC BY-SA 4.0 | null | 2010-07-28T14:37:17.337 | 2018-11-05T13:16:57.520 | 2018-11-05T13:16:57.520 | null | 549 | null |
908 | 2 | null | 880 | 6 | null | You miss one important issue -- there is almost never such thing as T[i]. Think of a simple problem in which the sum of two attributes (of a similar amplitude) is important; if you'd remove one of them the importance of the other will suddenly drop. Also, big amount of irrelevant attributes is the accuracy of most clas... | null | CC BY-SA 2.5 | null | 2010-07-28T14:58:10.173 | 2010-07-28T14:58:10.173 | null | null | null | null |
909 | 2 | null | 899 | 2 | null | This assumes that you don't even know if the second distribution is normal or not; I basically handle this uncertainty by focusing only on the normal distribution. This may or may not be the best approach.
If you can assume that the two populations are completely separated (i.e., all values from distribution A are less... | null | CC BY-SA 2.5 | null | 2010-07-28T15:24:38.010 | 2010-07-28T15:24:38.010 | null | null | 364 | null |
910 | 2 | null | 886 | 3 | null | There is a trivial answer -- there is no parameter estimation in machine learning! We don't assume that our models are equivalent to some hidden background models; we treat both reality and the model as black boxes and we try to shake the model box (train in official terminology) so that its output will be similar to t... | null | CC BY-SA 2.5 | null | 2010-07-28T15:29:33.070 | 2010-07-28T15:29:33.070 | null | null | null | null |
911 | 2 | null | 856 | 3 | null | Interesting question. What do you mean by weight?
I would be inclined to do a bootstrap...pick your favorite statistic (i.e. Fisher's Exact), and compute it on your data. Then assign new cells to each instance according to your null hypothesis, and repeat the process 999 times. This should give a pretty good empir... | null | CC BY-SA 2.5 | null | 2010-07-28T15:32:38.310 | 2010-07-28T15:32:38.310 | null | null | 549 | null |
912 | 2 | null | 868 | 1 | null | The other issue is that you put in your data, and the algorithm learns the weights and the Beta_0 for you...I don't know if Excel can do logistic regression...if it doesn't, I'd be inclined to use R to learn your model (and predict future cases for you!).
| null | CC BY-SA 2.5 | null | 2010-07-28T15:37:01.803 | 2010-07-28T15:37:01.803 | null | null | 549 | null |
913 | 1 | 916 | null | 5 | 718 | Comparing two variables, I came up with the following chart. the x, y pairs represent independent observations of data on the field. I've doen [Pearson correlation](http://en.wikipedia.org/wiki/Correlation_and_dependence) on it and have found one of 0.6.
My end goal is to establish a relationship between y and x such... | Relationships between two variables | CC BY-SA 2.5 | null | 2010-07-28T16:15:07.883 | 2010-09-19T01:47:02.270 | 2010-09-16T07:04:38.580 | null | 59 | [
"regression"
] |
914 | 2 | null | 913 | 3 | null | What you are looking for is called regression; there are a lot of methods you can do it, both statistical and machine learning ones. If you want to find f, you must use statistics; in that case you must first assume that f is of some form, like f:y=a*x+b and then use some regression method to fit the parameters.
The pl... | null | CC BY-SA 2.5 | null | 2010-07-28T16:21:41.483 | 2010-07-28T16:31:04.797 | 2010-07-28T16:31:04.797 | null | null | null |
915 | 2 | null | 913 | 3 | null | And just eyeballing the data, you are probably going to want to transform the data, as (at least to me) it looks skewed. Looking at the histograms of the two variables should suggest which transforms may be beneficial.
As suggested by mbq, more text [here](http://en.wikipedia.org/wiki/Data_transformation_%28statistics%... | null | CC BY-SA 2.5 | null | 2010-07-28T16:24:38.283 | 2010-07-28T16:48:05.950 | 2010-07-28T16:48:05.950 | 247 | 247 | null |
916 | 2 | null | 913 | 5 | null | Normality seems to be strongly violated at least by your y variable. I would log transform y to see if that cleans things up a bit. Then, fit a regression to log(y) ~ x. The formula the regression will return will be of the form log(y) = \alpha + \beta*x which you can transform back to the original scale by y = exp(\... | null | CC BY-SA 2.5 | null | 2010-07-28T16:31:53.143 | 2010-07-28T16:31:53.143 | null | null | 287 | null |
917 | 2 | null | 868 | 5 | null | Like drknexus said, for a logistic regression, your outcome measure needs to be 0 and 1. I'd go back and recode your outcome as 0 (didn't like it), or 1 (did like it). Then, abandon excel and load the data into R (it's really not as intimidating as it looks). Your regression will look something like this:
```
glm(Like... | null | CC BY-SA 2.5 | null | 2010-07-28T17:01:12.903 | 2010-07-28T17:01:12.903 | null | null | 287 | null |
918 | 2 | null | 898 | 3 | null | This area roughly falls into two categories. The first concerns stream processing and querying issues and associated models and algorithms. The second is efficient algorithms and models for learning from data streams (or data stream mining).
It's my impression that the CEP industry is connected to the first area. Fo... | null | CC BY-SA 2.5 | null | 2010-07-28T17:04:38.547 | 2010-07-28T20:07:08.813 | 2010-07-28T20:07:08.813 | 251 | 251 | null |
919 | 2 | null | 890 | 1 | null | I'm not sure I exactly understand your question, but I'm assuming your confusion involves a categorical predictor in your model. When it comes to continuous variables in a regression, the coefficients for each predictor are weights for the value of the predictor to produce the predicted y value:e.g. y = 2*x
However... | null | CC BY-SA 2.5 | null | 2010-07-28T17:14:08.763 | 2010-07-28T17:14:08.763 | null | null | 287 | null |
920 | 1 | 940 | null | 6 | 4729 | I completed a Monte Carlo simulation that consisted of one million ($10^6$) individual simulations. The simulation returns a variable, $p$, that can be either 1 or 0. I then weight the simulations based on predefined criteria and calculate the probability of $p$. I also calculate a risk ratio using $p$:
$$\text{Risk ra... | Test if probabilities are statistically different? | CC BY-SA 3.0 | null | 2010-07-28T17:15:09.090 | 2013-06-05T04:11:12.797 | 2013-06-05T04:11:12.797 | 805 | 559 | [
"hypothesis-testing"
] |
922 | 2 | null | 886 | 2 | null | I don't think there is a fundamental idea around parameter estimation in Machine Learning. The ML crowd will happily maximize the likelihood or the posterior, as long as the algorithms are efficient and predict "accurately". The focus is on computation, and results from statistics are widely used.
If you're looking f... | null | CC BY-SA 2.5 | null | 2010-07-28T17:28:47.880 | 2010-07-28T17:28:47.880 | 2017-04-13T12:44:33.550 | -1 | 251 | null |
924 | 1 | 926 | null | 7 | 828 | For 1,000,000 observations, I observed a discrete event, X, 3 times for the control group and 10 times for the test group. How do I determine for a large number of observations (1,000,000), if three is statistically different than ten?
| Determine if three is statistically different than ten for a very large number of observations (1,000,000) | CC BY-SA 2.5 | null | 2010-07-28T17:36:24.920 | 2010-10-08T16:05:48.613 | 2010-10-08T16:05:48.613 | 8 | 559 | [
"hypothesis-testing",
"large-data"
] |
925 | 2 | null | 924 | 0 | null | I would be really surprised if you find the difference statistically significant. Having said that you may want to use a test for a difference of proportions (3 out of 1M vs 10 out of 1M).
| null | CC BY-SA 2.5 | null | 2010-07-28T17:40:56.223 | 2010-07-28T17:40:56.223 | null | null | null | null |
926 | 2 | null | 924 | 5 | null | I think a simple chi-squared test will do the trick. Do you have 1,000,000 observations for both control and test? If so, your table of observations will be (in R code)
Edit: Woops! Left off a zero!
```
m <- rbind(c(3, 1000000-3), c(10, 1000000-10))
# [,1] [,2]
# [1,] 3 999997
# [2,] 10 999990
```
And chi... | null | CC BY-SA 2.5 | null | 2010-07-28T17:43:48.153 | 2010-07-28T17:51:05.423 | 2010-07-28T17:51:05.423 | 287 | 287 | null |
927 | 1 | 937 | null | 30 | 5970 | What are some podcasts related to statistical analysis? I've found some audio recordings of college lectures on ITunes U, but I'm not aware of any statistical podcasts. The closest thing I'm aware of is an operations research podcast [The Science of Better](http://www.scienceofbetter.org/podcast/). It touches on sta... | Statistical podcasts | CC BY-SA 2.5 | null | 2010-07-28T17:43:49.697 | 2016-12-17T07:00:37.593 | 2015-06-25T07:43:49.163 | 35989 | 319 | [
"references"
] |
928 | 1 | 932 | null | 7 | 8576 | This one is bothering me for a while, and a great dispute was held around it. In psychology (as well as in other social sciences), we deal with different ways of dealing with numbers :-) i.e. the levels of measurement. It's also common practice in psychology to standardize some questionnaire, hence transform the data i... | Measurement level of percentile scores | CC BY-SA 2.5 | null | 2010-07-28T17:57:51.697 | 2022-03-10T12:48:17.403 | 2010-08-07T17:48:50.100 | null | 1356 | [
"measurement"
] |
929 | 1 | null | null | 0 | 233 | How comprehensive is the following book - What interpretations are missing?
Interpretations of Probability, Andrei Khrennikov, 2009, de Gruyter, ISBN 978-3-11-020748-4
[http://www.degruyter.com/cont/fb/ma/detailEn.cfm?isbn=9783110207484&sel=pi](http://www.degruyter.com/cont/fb/ma/detailEn.cfm?isbn=9783110207484&sel=pi... | Probability Interpretations | CC BY-SA 2.5 | null | 2010-07-28T17:59:42.600 | 2010-07-28T19:14:49.470 | null | null | 560 | [
"probability"
] |
930 | 2 | null | 928 | 1 | null | Continuous (interval); this is a method how to convert ordinal data to something that may have some distribution that makes sense.
| null | CC BY-SA 2.5 | null | 2010-07-28T18:05:11.857 | 2010-07-28T18:05:11.857 | null | null | null | null |
931 | 2 | null | 927 | 6 | null | You may be interested in the following link: [http://www.ats.ucla.edu/stat/seminars/](http://www.ats.ucla.edu/stat/seminars/) where the UCLA Statistical Computing unit of the UCLA has very nice screen-casts available. I have found them very useful in the past. They function essentially as lectures. Top-quality teaching... | null | CC BY-SA 2.5 | null | 2010-07-28T18:17:46.900 | 2010-07-28T18:17:46.900 | null | null | 561 | null |
932 | 2 | null | 928 | 5 | null | Background to understand my answer
The critical property that distinguishes between ordinal and interval scale is whether we can take ratio of differences. While you cannot take ratio of direct measures for either scale the ratio of differences is meaningful for interval but not ordinal (See: [http://en.wikipedia.org/w... | null | CC BY-SA 3.0 | null | 2010-07-28T18:18:26.243 | 2016-04-30T22:16:44.757 | 2016-04-30T22:16:44.757 | 114097 | null | null |
933 | 2 | null | 290 | 4 | null | I have done very well with reading the official documentation. It is well-written, sometimes injected with humour (!) and, if you're willing to spend the time to learn Stata properly, is an absolute goldmine.
| null | CC BY-SA 2.5 | null | 2010-07-28T18:21:10.107 | 2010-07-28T18:21:10.107 | null | null | 561 | null |
934 | 2 | null | 886 | 18 | null | If statistics is all about maximizing likelihood, then machine learning is all about minimizing loss. Since you don't know the loss you will incur on future data, you minimize an approximation, ie empirical loss.
For instance, if you have a prediction task and are evaluated by the number of misclassifications, you coul... | null | CC BY-SA 3.0 | null | 2010-07-28T18:25:00.973 | 2017-08-29T15:26:29.920 | 2017-08-29T15:26:29.920 | 53690 | 511 | null |
935 | 2 | null | 929 | 2 | null | Though quantum probability and negative probability models are quite interesting, this is hardly exhaustive of nonstandard models of probability. There are for instance, [imprecise probability models](http://en.wikipedia.org/wiki/Imprecise_probability), and models that violate Kolmogorov's countable additivity axiom, ... | null | CC BY-SA 2.5 | null | 2010-07-28T18:36:09.920 | 2010-07-28T19:14:49.470 | 2010-07-28T19:14:49.470 | 39 | 39 | null |
936 | 2 | null | 927 | 7 | null | There is [econtalk](http://www.econtalk.org/), it is mostly about economics, but delves very often to issues of research, science, and statistics.
| null | CC BY-SA 2.5 | null | 2010-07-28T19:22:44.490 | 2010-07-28T19:22:44.490 | null | null | 253 | null |
937 | 2 | null | 927 | 14 | null | BBC's [More or Less](http://news.bbc.co.uk/2/hi/programmes/more_or_less/default.stm) is often concerned with numeracy and statistical literacy issues. But it's not specifically about statistics. Their [About](http://news.bbc.co.uk/2/hi/programmes/more_or_less/1628489.stm) page has some background.
>
More or Less is ... | null | CC BY-SA 2.5 | null | 2010-07-28T19:34:00.560 | 2010-07-28T19:34:00.560 | null | null | 251 | null |
939 | 1 | 941 | null | 4 | 1319 | Is the Yates' correction for continuity used only for 2X2 matrices?
| Yates' correction for continuity only for 2X2? | CC BY-SA 2.5 | null | 2010-07-28T20:43:33.327 | 2010-10-20T21:10:16.807 | 2010-10-20T21:10:16.807 | 8 | 559 | [
"contingency-tables",
"yates-correction"
] |
940 | 2 | null | 920 | 8 | null | If you have 1,000,000 independent "coin flips" that can produce 1 with probabilty (prob) and 0 with probability (1-prob), then the number of 1's observed will follow a [Binomial distribution](http://en.wikipedia.org/wiki/Binomial_distribution).
Tests of statistical significance are rejection tests, i.e. reject the hy... | null | CC BY-SA 2.5 | null | 2010-07-28T20:50:25.120 | 2010-07-28T21:19:40.940 | 2010-07-28T21:19:40.940 | 87 | 87 | null |
941 | 2 | null | 939 | 6 | null | It's derived for binomial/hypergeometric distributions, so it's applicable to 2x2 or 2x1 cases.
| null | CC BY-SA 2.5 | null | 2010-07-28T21:12:03.197 | 2010-07-28T21:12:03.197 | null | null | 251 | null |
942 | 1 | 962 | null | 27 | 12509 | I've been beginning to work my way through [Statistical Data Mining Tutorials by Andrew Moore](http://www.autonlab.org/tutorials/) (highly recommended for anyone else first venturing into this field). I started by reading this [extremely interesting PDF entitled "Introductory overview of time-series-based anomaly dete... | Application of wavelets to time-series-based anomaly detection algorithms | CC BY-SA 2.5 | null | 2010-07-28T21:13:23.387 | 2021-05-26T10:08:44.613 | 2011-02-08T16:48:14.277 | 223 | 75 | [
"time-series",
"outliers",
"signal-processing",
"wavelet"
] |
943 | 2 | null | 841 | 4 | null | If you can assume bivariate normality, then you can develop a likelihood-ratio test comparing the two possible covariance matrix structures. The unconstrained (H_a) maximum likelihood estimates are well known - just the sample covariance matrix, the constrained ones (H_0) can be derived by writing out the likelihood (a... | null | CC BY-SA 2.5 | null | 2010-07-28T21:31:14.630 | 2010-07-28T21:31:14.630 | null | null | 279 | null |
944 | 1 | 947 | null | 1 | 619 | When I type a left paren or any quote in the R console, it automatically creates a matching one to the right of my cursor. I guess the idea is that I can just type the expression I want inside without having to worry about matching, but I find it annoying, and would rather just type it myself. How can I disable this fe... | How can I get R to stop autocompleting my quotes/parens? | CC BY-SA 2.5 | null | 2010-07-28T21:45:46.273 | 2010-07-29T02:11:34.563 | null | null | null | [
"r"
] |
945 | 2 | null | 944 | 3 | null | Well either use a different IDE -- this is entirely a feature of the OS X app -- or try to configure the feature in question.
As for IDEs / R environments, I'm rather happy with [ESS](http://ess.r-project.org) which works on every platform R works on.
| null | CC BY-SA 2.5 | null | 2010-07-28T21:49:13.417 | 2010-07-28T21:49:13.417 | null | null | 334 | null |
946 | 1 | 963 | null | 3 | 2741 | New to the site. I am just getting started with R, and want to replicate a feature that is available in SPSS.
Simply, I build a "Custom Table" in SPSS with a single categorical variable in the column and many continuous/scale variables in the rows (no interactions, just stacked on top of each other).
The table rep... | Column Means Significance Tests in R | CC BY-SA 4.0 | null | 2010-07-28T21:50:29.093 | 2019-07-24T10:09:01.670 | 2019-07-24T10:09:01.670 | 11887 | 569 | [
"r",
"statistical-significance",
"spss",
"mean",
"multiple-comparisons"
] |
947 | 2 | null | 944 | 5 | null | On OSX, go to `R > Preferences > Editor` and deselect `Match braces/quotes`
| null | CC BY-SA 2.5 | null | 2010-07-28T21:51:15.083 | 2010-07-28T21:51:15.083 | null | null | 287 | null |
948 | 2 | null | 946 | 1 | null | ```
summary(df)
```
Will give you 5 number summaries and counts of `NA` for continuous variables, and counts for categorical variables.
As for the significance tests, you'll have to do that by hand with `t.test()` or `wilcox.test()`.
| null | CC BY-SA 2.5 | null | 2010-07-28T21:54:16.503 | 2010-07-28T21:54:16.503 | null | null | 287 | null |
949 | 1 | null | null | 37 | 30862 | Take $x \in \{0,1\}^d$ and $y \in \{0,1\}$ and suppose we model the task of predicting y given x using logistic regression. When can logistic regression coefficients be written in closed form?
One example is when we use a saturated model.
That is, define $P(y|x) \propto \exp(\sum_i w_i f_i(x_i))$, where $i$ indexes set... | When is logistic regression solved in closed form? | CC BY-SA 3.0 | null | 2010-07-28T21:59:02.693 | 2022-10-06T16:40:30.970 | 2012-09-20T12:49:01.220 | 2970 | 511 | [
"logistic",
"generalized-linear-model"
] |
950 | 2 | null | 373 | 5 | null | One does not need to know about conditional probability or Bayes Theorem to figure out that it is best to switch your answer.
Suppose you initially pick Door 1. Then the probability of Door 1 being a winner is 1/3 and the probability of Doors 2 or 3 being a winner is 2/3. If Door 2 is shown to be a loser by the hos... | null | CC BY-SA 2.5 | null | 2010-07-28T23:28:44.003 | 2010-07-28T23:28:44.003 | null | null | 99 | null |
951 | 1 | 1000 | null | 7 | 1366 | What is the relationship between a Nonhomogeneous Poisson process and a process that has heavy tail distribution for its inter arrival times?
Any pointer to a resource that can shed some light on this question would be hugely appreciated
| Nonhomogeneous Poisson and Heavy tail inter arrival time distribution | CC BY-SA 2.5 | null | 2010-07-29T00:48:11.603 | 2020-04-25T21:54:28.887 | 2020-04-25T21:54:28.887 | 11887 | 172 | [
"distributions",
"poisson-distribution",
"heavy-tailed"
] |
952 | 1 | null | null | 4 | 584 |
### Context
I have a survey of 16 questions, each with four possible responses. The purpose of the survey is to measure the respondent's propensity towards four categories (which we will denote A, B, C, D). Each of the four responses per question are representative of an aspect of the four categories, A, B, C, D.
Th... | How to reduce number of items on a multi-item scale where each item requires ranking four response options | CC BY-SA 3.0 | null | 2010-07-29T01:45:55.080 | 2018-10-01T06:01:52.400 | 2011-06-08T15:35:27.680 | 183 | 513 | [
"logistic",
"scales",
"survey",
"ranking"
] |
953 | 2 | null | 913 | 1 | null | I agree with the suggestions about running a regression possibly with log(y) as the outcome variable or some other suitable transformation. I just wanted to add one comment, if you are reporting the bivariate association, you might prefer:
(a) to correlate log(x) and log(y),
(b) Spearman's rho, which correlates the ran... | null | CC BY-SA 2.5 | null | 2010-07-29T02:00:32.547 | 2010-07-29T02:00:32.547 | null | null | 183 | null |
954 | 2 | null | 944 | 4 | null | To follow on from Dirk's comment, if you don't like your current IDE, check out some of the existing discussion on R IDEs:
[https://stackoverflow.com/questions/1439059/best-ide-texteditor-for-r](https://stackoverflow.com/questions/1439059/best-ide-texteditor-for-r)
| null | CC BY-SA 2.5 | null | 2010-07-29T02:11:34.563 | 2010-07-29T02:11:34.563 | 2017-05-23T12:39:27.620 | -1 | 183 | null |
955 | 1 | null | null | 1 | 1847 | Just wonder, is there any data analysis/ statistic/ data mining work that are available on freelance basis?
This could be subjective and argumentative, which is why I put it as CW.
| Data Analysis Work-- Is there Any Freelance Opportunity? | CC BY-SA 2.5 | null | 2010-07-29T03:25:03.290 | 2010-09-16T07:08:24.013 | 2010-09-16T07:08:24.013 | null | 175 | [
"careers"
] |
956 | 2 | null | 870 | 19 | null | As Robin said, you've got the Benjamini-Hochberg method backwards. With that method, you set a value for Q (upper case Q; the maximum desired FDR) and it then sorts your comparisons into two piles. The goal is that no more than Q% of the comparisons in the "discovery" pile are false, and thus at least 100%-Q% are true.... | null | CC BY-SA 3.0 | null | 2010-07-29T04:06:29.247 | 2013-03-07T01:26:38.717 | 2013-03-07T01:26:38.717 | 25 | 25 | null |
957 | 2 | null | 887 | 1 | null | I think you need to nail down the question you are asking, before you can compute an answer. I think this question is way too vague to answer: "test whether it is an vis-a-vis the general population".
The only question I think you can answer is this one: If the new value came from the same population as the others, wh... | null | CC BY-SA 2.5 | null | 2010-07-29T04:15:44.310 | 2010-07-29T04:15:44.310 | null | null | 25 | null |
958 | 2 | null | 955 | 1 | null | The short answer is "yes". Such work does exist.
For example, there is sometimes consulting work in and around universities.
Also, some companies wish to outsource data analysis and statistical activities.
In general, I found that word of mouth was a powerful tool. Once you build up a good reputation in a given communi... | null | CC BY-SA 2.5 | null | 2010-07-29T05:55:55.163 | 2010-07-29T05:55:55.163 | null | null | 183 | null |
959 | 2 | null | 952 | 2 | null | I've never had to perform such analyses, but there is an academic literature on the factor analysis of ipsative tests that would be relevant:
e.g.,
- Brown, A. (2016). Item response models for forced-choice questionnaires: A common framework. Psychometrika, 81(1), 135-160.
- Jackson, D. J., & Alwin, D. F. (1980). The... | null | CC BY-SA 4.0 | null | 2010-07-29T06:01:01.627 | 2018-10-01T06:01:52.400 | 2018-10-01T06:01:52.400 | 183 | 183 | null |
960 | 2 | null | 952 | 2 | null | So restructure your data merging all user responses, so in such form:
```
Q1 Q2 Q3 ...
user1 rank for option1 for Q1, user1 rank for option1 for Q2, ...
user1 rank for option2, ...
...
user2 rank for option1, ...
...
user325 rank for option4, ...
```
And then cluster the questions. I recommend agglomerative clustering... | null | CC BY-SA 2.5 | null | 2010-07-29T07:05:38.310 | 2010-07-29T07:05:38.310 | null | null | null | null |
961 | 1 | 971 | null | 12 | 6130 | I have a dataset made up of elements from three groups, let's call them G1, G2, and G3.
I analysed certain characteristics of these elements and divided them into 3 types of "behaviour" T1, T2, and T3 (I used cluster analysis to do that).
So, now I have a 3 x 3 contingency table like this with the counts of elements in... | Statistical test for n x m contingency tables | CC BY-SA 2.5 | null | 2010-07-29T07:07:36.513 | 2018-03-27T11:46:40.597 | 2010-09-16T06:54:07.353 | null | 582 | [
"contingency-tables"
] |
962 | 2 | null | 942 | 19 | null | Wavelets are useful to detect singularities in a signal (see for example the paper [here](http://www.math.u-bordeaux1.fr/~jbigot/Site/Publications_files/Spectrometry.pdf) (see figure 3 for an illustration) and the references mentioned in this paper. I guess singularities can sometimes be an anomaly?
The idea here is ... | null | CC BY-SA 3.0 | null | 2010-07-29T07:10:39.967 | 2015-05-29T10:54:19.570 | 2015-05-29T10:54:19.570 | -1 | 223 | null |
963 | 2 | null | 946 | 3 | null | As I read in help for the `t.test`, it is only applicable for the 2-sample tests. If you want to perform it to every combination of the columns of a matrix A, taken 2 at a time, you could do something like this (for the moment, I can't recall a better way)
```
apply(combn(1:dim(A)[2],2),2,function(x) t.test(A[,x[1]],A[... | null | CC BY-SA 2.5 | null | 2010-07-29T08:15:59.907 | 2010-07-29T08:22:43.180 | 2010-07-29T08:22:43.180 | 339 | 339 | null |
964 | 1 | 1011 | null | 4 | 453 | So in R, for instance, this would be:
```
my_ts_logged_diffed = diff(log(some_ts_object))
plot(my_ts_logged_diffed)
```
This seems to be part of every experienced analyst/forecaster analytical workflow--in particular, a visual examination of the plotted data. What are they looking for--i.e., what useful information do... | What are analysts looking for when they plot a differenced, logged time series? | CC BY-SA 2.5 | null | 2010-07-29T08:28:36.520 | 2010-11-02T01:47:17.577 | 2010-07-31T00:48:08.403 | 159 | 438 | [
"time-series",
"data-transformation"
] |
965 | 2 | null | 964 | 4 | null | Most growth/decay processes will at most change the moving quantity at an exponential rate. The differences of the logs of the quantity relate to the local slope λ, so for a underlying exponential growth or decay process it would be flat in t. Any deviation from flat gives you hints if and where there are switchovers b... | null | CC BY-SA 2.5 | null | 2010-07-29T08:46:34.730 | 2010-07-29T08:46:34.730 | null | null | 56 | null |
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