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2823 | 1 | null | null | 4 | 291 | I've just been given a stack of polling data to analyse. Some of the questions are obviously leading or present subtle incentives (for the poller or polled) for specific answers. Of other questions I'm not so sure but I have some doubts. I'm also starting to question other factors about how the poll was conducted (envi... | What are good resources/criteria for judging human bias in data collection? | CC BY-SA 2.5 | null | 2010-09-18T16:14:02.140 | 2010-09-19T09:30:23.640 | 2010-09-19T09:30:23.640 | 183 | 1343 | [
"references",
"mathematical-statistics",
"survey"
] |
2824 | 1 | 2853 | null | 17 | 4509 | A few months ago I posted a question about homoscedasticity tests in R on SO, and Ian Fellows answered that (I'll paraphrase his answer very loosely):
Homoscedasticity tests are not a good tool when testing the goodness of fit of your model. With small samples, you don't have enough power to detect departures from ho... | Checking ANOVA assumptions | CC BY-SA 3.0 | null | 2010-09-18T17:42:06.037 | 2016-03-11T12:36:01.467 | 2016-03-11T12:29:57.890 | 4253 | 1356 | [
"hypothesis-testing",
"anova",
"nonparametric",
"goodness-of-fit",
"heteroscedasticity"
] |
2825 | 2 | null | 2715 | 53 | null | Keep your analysis reproducible. A reviewer or your boss or someone else will eventually ask you how exactly you arrived at your result - probably six months or more after you did the analysis. You will not remember how you cleaned the data, what analysis you did, why you chose the specific model you used... And recons... | null | CC BY-SA 3.0 | null | 2010-09-18T18:15:49.220 | 2013-06-17T18:03:39.020 | 2013-06-17T18:03:39.020 | 22047 | 1352 | null |
2826 | 2 | null | 2823 | 1 | null | Possibly [Benford's Law](http://en.wikipedia.org/wiki/Benford%27s_law) might help. Check the Application section on the wiki
| null | CC BY-SA 2.5 | null | 2010-09-18T18:33:13.560 | 2010-09-18T20:43:30.903 | 2010-09-18T20:43:30.903 | 795 | 364 | null |
2827 | 2 | null | 2715 | 8 | null | For histograms, a good rule of thumb for number of bins in a histogram:
square root of the number of data points
| null | CC BY-SA 2.5 | null | 2010-09-18T19:49:37.593 | 2010-09-18T19:49:37.593 | null | null | 438 | null |
2828 | 1 | 2890 | null | 24 | 14703 | How can we compare complexity of two models with the same number of parameters?
Edit 09/19: To clarify, model complexity is a measure of how hard it is to learn from limited data. When two models fit existing data equally well, a model with lower complexity will give lower error on future data. When approximations are ... | Measures of model complexity | CC BY-SA 2.5 | null | 2010-09-18T20:20:10.293 | 2017-06-09T02:49:27.430 | 2010-09-19T22:06:26.193 | 511 | 511 | [
"model-selection"
] |
2829 | 2 | null | 527 | 1 | null | I agree with @drnexus. In addition, I might recommend a Morgan-Pitman test for the equality of variances of the two methods. This would tell you if one method has more variance than the other. This in itself might not be a bad thing because presumably the two tests have different bias-variance tradeoffs (for example, o... | null | CC BY-SA 2.5 | null | 2010-09-18T20:41:05.413 | 2010-09-18T20:41:05.413 | null | null | 795 | null |
2830 | 2 | null | 2828 | 5 | null | I think it would depend on the actual model fitting procedure. For a generally applicable measure, you might consider Generalized Degrees of Freedom described in [Ye 1998](http://www.jstor.org/pss/2669609) -- essentially the sensitivity of change of model estimates to perturbation of observations -- which works quite ... | null | CC BY-SA 2.5 | null | 2010-09-18T20:41:57.250 | 2010-09-18T20:41:57.250 | null | null | 251 | null |
2831 | 2 | null | 2715 | 30 | null | One rule per answer ;-)
Talk to the statistician before conducting the study. If possible, before applying for the grant. Help him/her understand the problem you are studying, get his/her input on how to analyze the data you are about to collect and think about what that means for your study design and data requirement... | null | CC BY-SA 2.5 | null | 2010-09-18T21:07:17.487 | 2010-09-18T21:07:17.487 | null | null | 1352 | null |
2832 | 2 | null | 1815 | 4 | null | [Experimental Design for the Life Sciences](http://ukcatalogue.oup.com/product/9780199285112.do), by Ruxton & Colegrave. Aimed primarily at undergraduates.
| null | CC BY-SA 2.5 | null | 2010-09-18T21:07:17.843 | 2010-09-18T21:07:17.843 | null | null | 266 | null |
2833 | 2 | null | 2824 | 11 | null | A couple of graphs will usually be much more enlightening than the p value from a test of normality or homoskedasticity. Plot observed dependent variables against independent variables. Plot observations against fits. Plot residuals against independent variables. Investigate anything that looks strange on these plots. ... | null | CC BY-SA 2.5 | null | 2010-09-18T21:27:13.180 | 2010-09-18T21:27:13.180 | null | null | 1352 | null |
2834 | 2 | null | 527 | 16 | null | The simple correlation approach isn't the right way to analyze results from method comparison studies. There are (at least) two highly recommended books on this topic that I referenced at the end (1,2). Briefly stated, when comparing measurement methods we usually expect that (a) our conclusions should not depend on th... | null | CC BY-SA 3.0 | null | 2010-09-18T21:29:59.203 | 2016-07-13T08:11:16.300 | 2016-07-13T08:11:16.300 | 1352 | 930 | null |
2835 | 2 | null | 2585 | 2 | null | A slight variation on Jeromy's theme: time on the horizontal axis, price on the vertical axis. Plot multiple lines: one connecting the minimum prices, one connecting the 10% quantiles of prices, one connecting the 25% quantiles of prices. Plot these lines in varying shades of gray: large amounts of product available at... | null | CC BY-SA 4.0 | null | 2010-09-18T21:46:28.497 | 2023-03-09T10:11:48.967 | 2023-03-09T10:11:48.967 | 362671 | 1352 | null |
2836 | 2 | null | 2828 | 3 | null | [Minimum Description Length](http://en.wikipedia.org/wiki/Minimum_description_length) may be an avenue worth pursuing.
| null | CC BY-SA 2.5 | null | 2010-09-18T21:50:53.100 | 2010-09-18T21:50:53.100 | null | null | 1352 | null |
2837 | 2 | null | 113 | 2 | null | John, I am not sure my suggestion may be of help. But, in any case the book [Intuitive Biostatistics](http://rads.stackoverflow.com/amzn/click/0199730067) by Harvey Motulsky may be of assistance. Chapter 37 'Choosing a Test' has a pretty good table on page 298 that tells you given the nature of the data set and probl... | null | CC BY-SA 2.5 | null | 2010-09-19T00:27:18.983 | 2010-10-08T23:57:02.170 | 2010-10-08T23:57:02.170 | 1329 | 1329 | null |
2838 | 2 | null | 913 | 1 | null | Many have already made excellent suggestions regarding transforming the variables and using robust regression methods. But, when looking at the scatter plot, I observe two separate data sets. One set has a very strong linear relationship where the correlation is a lot higher than the overall 0.6. And, visually it lo... | null | CC BY-SA 2.5 | null | 2010-09-19T00:52:52.930 | 2010-09-19T00:52:52.930 | null | null | 1329 | null |
2839 | 2 | null | 913 | 0 | null | Like the others have said, some sort of transformation is recommended. Your data seems highly clustered, and could be roughly linear, but it's difficult to tell with all the other points around it.
Others have suggested trying a log transformation, but it might also be a good idea to try a [Box-Cox Transformation](http... | null | CC BY-SA 2.5 | null | 2010-09-19T01:47:02.270 | 2010-09-19T01:47:02.270 | null | null | 1118 | null |
2840 | 2 | null | 2824 | 4 | null | QQ Plots are pretty good ways to detect non-normality.
For homoscedasticity, try Levene's test or a Brown-Forsythe test. Both are similar, though BF is a little more robust. They are less sensitive to non-normality than Bartlett's test, but even still, I've found them not to be the most reliable with small sample size... | null | CC BY-SA 3.0 | null | 2010-09-19T02:09:59.820 | 2016-03-11T12:36:01.467 | 2016-03-11T12:36:01.467 | 22047 | 1118 | null |
2841 | 2 | null | 2823 | 4 | null | In regards to the leading questions, here are several options of how I would attempt to investigate if your suspicions are true;
1 - Conduct your own experiment. One of your conditions will be to mimic the leading questions in the prior surveys, the other condition will be a survey constructed with functionally similar... | null | CC BY-SA 2.5 | null | 2010-09-19T03:24:26.727 | 2010-09-19T03:24:26.727 | null | null | 1036 | null |
2842 | 2 | null | 2824 | 4 | null | The are some very good web guides to checking the assumptions of ANOVA & what to do if the fail. [Here](http://quality-control-plan.com/StatGuide/oneway_anova_ass_viol.htm) is one. [This](http://homepage.mac.com/bradthiessen/stats/m301/4a.pdf) is another.
Essentially your eye is the best judge, so do some [explorator... | null | CC BY-SA 2.5 | null | 2010-09-19T04:34:21.487 | 2010-09-19T04:34:21.487 | null | null | 521 | null |
2843 | 2 | null | 328 | 0 | null | I like [Risk and Asset Allocation](http://books.google.com/books?id=Qc8KWWtUokcC&lpg=PR1&dq=risk%20and%20asset%20allocation%20meucci&pg=PR1#v=onepage&q&f=false) by A. Meucci. This book is a bit more advanced than Ruppert's book, but still very user-friendly.
| null | CC BY-SA 2.5 | null | 2010-09-19T05:41:03.267 | 2010-09-19T05:41:03.267 | null | null | 795 | null |
2844 | 1 | 2847 | null | 11 | 8113 | Example code:
```
(pc.cr <- princomp(USArrests))
summary(pc.cr)
loadings(pc.cr) ## note that blank entries are small but not zero
```
I am getting different outputs from each, and I am not sure I understand what the difference is.
Here is the output:
```
> summary(pc.cr)
Importance of components:
... | What is the difference between summary() and loadings() for princomp() object in R? | CC BY-SA 3.0 | null | 2010-09-19T09:21:07.803 | 2016-05-24T20:54:37.147 | 2016-05-24T20:54:37.147 | 253 | 253 | [
"r",
"pca"
] |
2845 | 2 | null | 1815 | 2 | null | [Experimental Design in Biotechnology](http://rads.stackoverflow.com/amzn/click/0824778812) by Perry D. Haaland, ed Marcel Dekker.
| null | CC BY-SA 2.5 | null | 2010-09-19T09:24:48.077 | 2010-09-19T09:34:20.480 | 2010-09-19T09:34:20.480 | null | null | null |
2846 | 1 | 2850 | null | 13 | 10140 | I have read and seen a lot of Parallel coordinates plots. Can someone answer the following set of questions:
- What are parallel coordinates plots (PCP) in simple words, so that a layman can understand?
- A mathematical explanation with some intuition if possible
- When are PCP useful and when to use them?
- When a... | An easy explanation for the parallel coordinates plot | CC BY-SA 2.5 | null | 2010-09-19T09:32:28.610 | 2014-05-04T04:23:06.427 | 2010-09-19T09:37:17.790 | 183 | 1307 | [
"r",
"data-visualization"
] |
2847 | 2 | null | 2844 | 4 | null | The first output is the correct and most useful one. Calling `loadings()` on your object just returns a summary where the SS are always equal to 1, hence the % variance is just the SS loadings divided by the number of variables. It makes sense only when using Factor Analysis (like in `factanal`). I never use `princomp`... | null | CC BY-SA 2.5 | null | 2010-09-19T10:45:31.837 | 2010-09-19T11:40:21.617 | 2010-09-19T11:40:21.617 | 930 | 930 | null |
2848 | 2 | null | 1708 | 3 | null | It looks like you are referring to eigenanalysis for SNPs data and the article from Nick Patterson, [Population Structure and Eigenanalysis](http://www.plosgenetics.org/article/info%3adoi/10.1371/journal.pgen.0020190) (PLoS Genetics 2006), where the first component explains the largest variance on allele frequency wrt.... | null | CC BY-SA 2.5 | null | 2010-09-19T11:24:58.573 | 2010-09-26T20:55:20.310 | 2010-09-26T20:55:20.310 | 930 | 930 | null |
2849 | 1 | null | null | 3 | 718 | I have a static panel data model with small T (T=5) that makes it impossible for me to use granger causality as it requires a long time span.
So my question:
- Is there any alternative solution to test for causation even in a small T context?
Any hint will be highely appreciated!
| How to test for causation in a static panel data model with small t? | CC BY-SA 2.5 | null | 2010-09-19T12:46:28.310 | 2010-11-10T07:40:11.763 | 2010-11-10T07:40:11.763 | 930 | 1251 | [
"econometrics",
"causality",
"panel-data"
] |
2850 | 2 | null | 2846 | 6 | null | It seems to me that the main function of PCP is to highlight homogeneous groups of individuals, or conversely (in the dual space, by analogy with PCA) specific patterns of association on different variables. It produces an effective graphical summary of a multivariate data set, when there are not too much variables. Va... | null | CC BY-SA 2.5 | null | 2010-09-19T12:57:26.100 | 2010-09-19T16:55:34.567 | 2017-04-13T12:44:40.807 | -1 | 930 | null |
2851 | 2 | null | 2446 | 2 | null | Concerning your more specific question (i.e. how many degrees of freedom): the question is how many replicates do you have. Look at the early pages of chapter 19 of [the R book](http://rads.stackoverflow.com/amzn/click/0470510242) for examples and guidelines for such accounting.
We could do the accounting here but i do... | null | CC BY-SA 2.5 | null | 2010-09-19T13:21:39.003 | 2010-09-21T20:33:56.847 | 2010-09-21T20:33:56.847 | 603 | 603 | null |
2852 | 1 | null | null | 1 | 5555 | The biological data is listed as following:
```
V1 V2 V3 V4 V5 V6
0.064 0.014 0.016 0.012 0.013 0.023
0.056 0.000 0.000 0.008 0.010 0.000
0.042 0.014 0.024 0.008 0.017 0.023
0.031 0.014 0.016 0.008 0.013 0.023
0.068 0.000 0.008 0.004 0.020 0.000
0.081 0.000 0.000 0.004 0.010 0.000
0.060 0.014 0.016 0... | How to analyze these data? | CC BY-SA 2.5 | null | 2010-09-19T14:02:26.617 | 2010-09-20T11:29:59.137 | 2010-09-20T06:33:04.833 | 930 | null | [
"r",
"hypothesis-testing"
] |
2853 | 2 | null | 2824 | 12 | null | In applied settings it is typically more important to know whether any violation of assumptions is problematic for inference.
Assumption tests based on significance tests are rarely of interest in large samples, because most inferential tests are robust to mild violations of assumptions.
One of the nice features of g... | null | CC BY-SA 2.5 | null | 2010-09-19T14:44:17.667 | 2010-09-19T14:44:17.667 | null | null | 183 | null |
2854 | 1 | 5646 | null | 5 | 1274 | Dear all,
I was encouraged to ask this question here as well as on stackoverflow and would be very appreciative of any answers...
Due to hetereoscedasticity I'm doing bootstrapped linear regression (appeals more to me than robust regression). I'd like to create a plot along the lines of what I've done in the script he... | Calculating probability for bivariate normal distributions based on bootstrapped regression coefficients | CC BY-SA 2.5 | null | 2010-09-19T15:00:04.550 | 2010-12-24T11:45:34.523 | 2010-12-19T17:06:45.113 | 449 | 1291 | [
"r",
"bootstrap",
"heteroscedasticity",
"ggplot2"
] |
2855 | 2 | null | 2010 | 2 | null | Almost all statistics implicitly condition on N. We treat N as a constant that can come out from the expression $\mathbb{E}\left[\frac{1}{N}\sum_{i=1}^{N}{x_i}\right]$, for example. For that to be appropriate, N has to be a fixed value, which we get by conditioning. Without conditioning on N, as you said, we'd need to ... | null | CC BY-SA 2.5 | null | 2010-09-19T16:41:11.350 | 2010-09-19T16:41:11.350 | null | null | 401 | null |
2856 | 2 | null | 2846 | 4 | null | In regards to questions 3, 4, and 5 I would suggest you check out this work
[Perceiving patterns in parallel coordinates: determining thresholds for identification of relationships
by: Jimmy Johansson, Camilla Forsell, Mats Lind, Matthew Cooper in
Information Visualization, Vol. 7, No. 2. (2008), pp. 152-162.](http://... | null | CC BY-SA 2.5 | null | 2010-09-19T17:10:15.873 | 2010-09-19T17:28:17.197 | 2010-09-19T17:28:17.197 | 1036 | 1036 | null |
2857 | 2 | null | 2852 | 1 | null | For most of your variables (e.g. `V2`), some observations have identical values, hence the warning message thrown by R: unique ranks cannot be computed for all observations, and there are ties, precluding the computation of an exact p-value. For your variable named `V2`, there are in fact only two distinct values (out ... | null | CC BY-SA 2.5 | null | 2010-09-19T17:36:12.660 | 2010-09-19T17:36:12.660 | null | null | 930 | null |
2858 | 2 | null | 2846 | 4 | null | Please visit [http://www.cs.tau.ac.il/~aiisreal/](http://www.cs.tau.ac.il/~aiisreal/) and also look at the new book
Parallel Coordinates - This book is about visualization, systematically incorporating
the fantastic human pattern recognition into the problem-solving process...
www.springer.com/math/cse/book/978-0-387-2... | null | CC BY-SA 2.5 | null | 2010-09-19T17:57:05.217 | 2010-09-19T17:57:05.217 | null | null | 1366 | null |
2859 | 2 | null | 2852 | 5 | null | Sometimes a formal statistical test is overkill. Row by row, the entries in the first column are the largest. Draw a picture to make this apparent: side-by-side boxplots or dotplots would work nicely.
Although this is a post-hoc comparison, if the initial intent had been to compare the first column against the rest f... | null | CC BY-SA 2.5 | null | 2010-09-19T18:11:38.943 | 2010-09-19T18:11:38.943 | null | null | 919 | null |
2860 | 1 | null | null | 5 | 3572 | We know that the projection matrix learned by PCA can be applied to out-of-sample data points to get their low-dimensional embedding. However, how reliable are these embeddings expected to be, as compared to the embedding obtained from PCA with these out-of-sample points combined with the original data?
Consider this ... | PCA on out-of-sample data | CC BY-SA 2.5 | null | 2010-09-19T18:53:35.410 | 2022-05-03T12:10:00.487 | 2010-09-21T12:01:56.170 | 183 | 881 | [
"machine-learning",
"pca",
"dimensionality-reduction"
] |
2861 | 2 | null | 2615 | 0 | null | I am not sure what the real question is, but suppose instead of changing every non-diagonal element, you changed just 2 (to keep the resulting matrix symmetric). That is let $\hat{C}$ be $C$ with $\hat{C_{i,j}} = C_{i,j} + \Delta C / 2= \hat{C_{j,i}},$ for some choice of $i,j$ with $i \ne j$. (alternatively, imagine $\... | null | CC BY-SA 2.5 | null | 2010-09-19T20:09:26.417 | 2010-09-20T01:50:20.380 | 2010-09-20T01:50:20.380 | 795 | 795 | null |
2863 | 1 | 2864 | null | 6 | 13782 | I want to assess item-total correlations on a 19-item questionnaire (some of the questions are meant to be reverse-scored). My question is:
- Do I reverse score the items PRIOR to calculating the item-total correlations (in order to eliminate any variables that do not correlate with the total at >.40)?
- Addition... | Should I reverse score items before running reliability analyses (item-total correlation) and factor analysis? | CC BY-SA 3.0 | null | 2010-09-19T22:35:50.730 | 2020-02-29T20:40:23.440 | 2011-06-06T13:54:23.937 | 183 | null | [
"correlation",
"factor-analysis",
"reliability"
] |
2864 | 2 | null | 2863 | 5 | null | Yes, you should reverse score all items as needed to ensure that a particular score means the same thing on all items. You should do this for all types of analysis.
For example, you have 'propensity to shoplift' measured via 3 items on a scale of 1 to 5 (where 1 is low propensity to shoplift and 5 is high). Suppose th... | null | CC BY-SA 2.5 | null | 2010-09-19T22:56:29.170 | 2010-09-19T22:56:29.170 | null | null | null | null |
2872 | 2 | null | 195 | 2 | null | I have been told many times that the Anderson Darling (AD) test is much better than the Kolmogorov-Smirnov (KS) one because AD does a better job at fitting the tails of the distribution. KS is only good at fitting the mid-range of the distribution; but, is not better than AD even in this regard. I think the main adva... | null | CC BY-SA 2.5 | null | 2010-09-20T00:29:57.047 | 2010-09-20T00:29:57.047 | null | null | 1329 | null |
2873 | 2 | null | 2860 | 1 | null | I have never done this but my intuition suggests that the answer would depend to the extent to which the covariance matrix for the 500 data points is 'different' from the out-of-sample data. If the out-of-sample covariance matrix is very different then clearly the projection matrix of those points would be different th... | null | CC BY-SA 2.5 | null | 2010-09-20T00:38:48.693 | 2010-09-20T00:38:48.693 | null | null | null | null |
2875 | 1 | null | null | 3 | 261 | My friend and I are working on a project on distributed datastructures. We were wondering how much is nearest neighbor information used in modern recommendation systems and whether it would be worthwhile to work on a distributed datastructure (say a kd-tree) for that purpose.
Thanks
| Nearest neighbor information for recommendation engines | CC BY-SA 2.5 | null | 2010-09-20T01:19:26.897 | 2013-08-20T00:03:06.297 | 2013-08-20T00:03:06.297 | 22468 | 250 | [
"k-nearest-neighbour",
"recommender-system"
] |
2877 | 2 | null | 2860 | 2 | null | This isn't unlike a model selection problem where the goal is to arrive at something close to the "true dimensionality" of the data. You could try a cross validation approach, say 5-fold CV with your 500 data points. This will give you a reasonable metric of generalization error for out-of-sample data. The following... | null | CC BY-SA 4.0 | null | 2010-09-20T03:38:03.447 | 2022-05-03T12:10:00.487 | 2022-05-03T12:10:00.487 | 79696 | 251 | null |
2878 | 2 | null | 2863 | 9 | null | Reliability Analysis: Yes, you should reverse score the reversed items.
Factor Analysis: It does not matter so much. Eigenvalues and associated indices (e.g., variance explained by factors, rules of thumb regarding number of factors to extract, etc.) should be the same. The sign of factor loadings will flip based on wh... | null | CC BY-SA 2.5 | null | 2010-09-20T04:07:18.163 | 2010-09-20T04:07:18.163 | null | null | 183 | null |
2883 | 2 | null | 2061 | 4 | null | [BIOSTATISTICS VS. LAB RESEARCH](http://www.xtranormal.com/watch/6878253/):
A funny/sad video on statistics consulting.
| null | CC BY-SA 2.5 | null | 2010-09-20T06:05:15.013 | 2010-09-20T10:34:39.257 | 2010-09-20T10:34:39.257 | 183 | 183 | null |
2884 | 2 | null | 2852 | 0 | null | Thank you very much, chl, whuber and Gaetan Lion. But do you think is there any problem that if I change to caculate the differene among the data using Kruskal-Wallis test instead of comparing the difference between the first column with other columns?
>
kruskal.test(as.list(Data))
```
Kruskal-Wallis rank sum te... | null | CC BY-SA 2.5 | null | 2010-09-20T06:14:15.227 | 2010-09-20T11:29:59.137 | 2010-09-20T11:29:59.137 | null | null | null |
2885 | 2 | null | 2828 | 5 | null | Minimum Description Length (MDL) and Minimum Message Length (MML) are certainly worth checking out.
As far as MDL is concerned, a simple paper that illustrates the Normalized Maximum Likelihood (NML) procedure as well as the asymptotic approximation is:
>
S. de Rooij & P. Grünwald. An empirical
study of minimum desc... | null | CC BY-SA 2.5 | null | 2010-09-20T06:20:50.417 | 2010-09-20T06:20:50.417 | null | null | 530 | null |
2886 | 1 | 2887 | null | 8 | 10898 | As title, I am thinking of merging both into "missing data", which is to name it as NA in R. Since I don't see it will make much sense (or even any sense), to separate the "don't know" row out and to compare the information with other rows.
Is it OK for me to do so?
| How will you deal with "don't know" and "missing data" in survey data? | CC BY-SA 4.0 | null | 2010-09-20T06:44:20.220 | 2019-07-25T10:10:37.353 | 2019-07-25T10:10:37.353 | 11887 | 588 | [
"multivariate-analysis",
"missing-data",
"survey"
] |
2887 | 2 | null | 2886 | 12 | null | Well, you should also considered that "don't know" is at least some kind of answer, whereas non-response is a purely missing value. Now, we often allow for "don't know" response in survey just to avoid forcing people to provide a response anyway (which might bias the results). For example, in the National Health and Nu... | null | CC BY-SA 2.5 | null | 2010-09-20T07:08:01.583 | 2010-09-20T07:08:01.583 | null | null | 930 | null |
2888 | 2 | null | 1856 | 8 | null | I haven't seen this used in outside of bioinformatics/machine learning either, but maybe you can be the first one :)
As a good representative of small sample method method from bioinformatics, logistic regression with L1 regularization can give a good fit when number of parameters is exponential in the number of observ... | null | CC BY-SA 2.5 | null | 2010-09-20T07:29:51.983 | 2010-10-01T15:56:38.640 | 2010-10-01T15:56:38.640 | 511 | 511 | null |
2889 | 2 | null | 2886 | 2 | null | It depends on the type of question/response in your survey. If they are like "I like", "I dislike", "Don't know", chl answers partially to your question.
The first solution is chl's answer. You have to check if "Don't know" doesn't hide anything. You have to analyse separately these values to see if it highlights a sp... | null | CC BY-SA 2.5 | null | 2010-09-20T07:31:33.540 | 2010-09-20T07:39:17.980 | 2010-09-20T07:39:17.980 | 930 | 1154 | null |
2890 | 2 | null | 2828 | 13 | null | Besides the various measures of Minimum Description Length (e.g., normalized maximum likelihood, Fisher Information approximation), there are two other methods worth to mention:
- Parametric Bootstrap. It's a lot easier to implement than the demanding MDL measures. A nice paper is by Wagenmaker and colleagues:
Wagen... | null | CC BY-SA 2.5 | null | 2010-09-20T08:40:00.997 | 2010-09-21T08:45:45.537 | 2017-04-13T12:44:23.203 | -1 | 442 | null |
2891 | 1 | 5695 | null | 1 | 188 | I'm looking for a simple way to store ratios.
For a time component, I must store the average ratio between two behavior. For example the number of people that turn left compared to the number of people that turn right.
I have to detect unusual behavior (people that turn right abnormally).
How should I mathematically co... | Best value to store ratio data and compare it to time period average | CC BY-SA 2.5 | null | 2010-09-20T09:07:06.277 | 2010-12-22T14:22:27.143 | 2010-12-22T14:22:27.143 | 1739 | null | [
"data-visualization",
"multiple-comparisons",
"count-data",
"logit",
"proportion"
] |
2892 | 1 | 2905 | null | 17 | 14638 | What is your intuition / interpretation of a distribution of eigenvalues of a correlation matrix? I tend to hear that usually 3 largest eigenvalues are the most important, while those close to zero are noise. Also, I've seen a few research papers investigating how naturally occuring eigenvalue distributions differ from... | Intuition / interpretation of a distribution of eigenvalues of a correlation matrix? | CC BY-SA 2.5 | null | 2010-09-20T10:26:08.910 | 2019-02-17T00:32:01.113 | null | null | 1250 | [
"distributions",
"correlation"
] |
2893 | 1 | 2897 | null | 21 | 5825 | It is usual to use second, third and fourth moments of a distribution to describe certain properties. Do partial moments or moments higher than the fourth describe any useful properties of a distribution?
| Moments of a distribution - any use for partial or higher moments? | CC BY-SA 2.5 | null | 2010-09-20T10:56:57.297 | 2018-09-04T08:41:06.673 | 2018-09-04T08:41:06.673 | 11887 | 1250 | [
"distributions",
"moments",
"partial-moments"
] |
2894 | 1 | null | null | 9 | 415 | I am trying to estimate the mean of a more-or-less Gaussian distribution via sampling. I have no prior knowledge about its mean or its variance. Each sample is expensive to obtain. How do I dynamically decide how many samples I need to get a certain level of confidence/accuracy? Alternatively, how do I know when I can ... | Dynamic calculation of number of samples required to estimate the mean | CC BY-SA 2.5 | null | 2010-09-20T13:24:09.147 | 2010-09-20T15:51:22.327 | 2010-09-20T13:29:12.717 | 1376 | 1376 | [
"estimation",
"sample-size"
] |
2895 | 2 | null | 665 | 6 | null | Probability studies, well, how probable events are. You intuitively know what probability is.
Statistics is the study of data: showing it (using tools such as charts), summarizing it (using means and standard deviations etc.), reaching conclusions about the world from which that data was drawn (fitting lines to data et... | null | CC BY-SA 2.5 | null | 2010-09-20T13:59:30.777 | 2010-09-20T13:59:30.777 | null | null | 666 | null |
2896 | 2 | null | 2894 | 0 | null | You would normally want at least 30 to invoke central limit theorem (though this is somewhat arbitrary). Unlike in the case with polls etc, which are modelled using the binomial distribution, you can not determine a sample size beforehand which guarantees a level of accuracy with a Gaussian process - it depends on what... | null | CC BY-SA 2.5 | null | 2010-09-20T15:19:18.547 | 2010-09-20T15:44:52.563 | 2010-09-20T15:44:52.563 | 229 | 229 | null |
2897 | 2 | null | 2893 | 10 | null | Aside from special properties of a few numbers (e.g., 2), the only real reason to single out integer moments as opposed to fractional moments is convenience.
Higher moments can be used to understand tail behavior. For example, a centered random variable $X$ with variance 1 has subgaussian tails (i.e. $\mathbb{P}(|X| >... | null | CC BY-SA 2.5 | null | 2010-09-20T15:22:46.340 | 2011-03-24T18:26:30.237 | 2011-03-24T18:26:30.237 | 89 | 89 | null |
2898 | 2 | null | 2894 | 2 | null | You need to search for 'Bayesian adaptive designs'. The basic idea is as follows:
- You initialize the prior for the parameters of interest.
Before any data collection your priors would be diffuse. As additional data comes in you re-set the prior to be the posterior that corresponds to the 'prior + data till that poi... | null | CC BY-SA 2.5 | null | 2010-09-20T15:51:22.327 | 2010-09-20T15:51:22.327 | null | null | null | null |
2899 | 2 | null | 2893 | 10 | null | I get suspicious when I hear people ask about third and fourth moments. There are two common errors people often have in mind when they bring up the topic. I'm not saying that you are necessarily making these mistakes, but they do come up often.
First, it sounds like they implicitly believe that distributions can be b... | null | CC BY-SA 2.5 | null | 2010-09-20T15:54:47.243 | 2010-09-20T17:31:39.423 | 2010-09-20T17:31:39.423 | 319 | 319 | null |
2900 | 2 | null | 1805 | 9 | null | [This page in MathWorld](http://mathworld.wolfram.com/FishersExactTest.html)
explains how the calculations work. It points out that the test can be defined in a variety of ways:
>
To compute the P-value of the test,
the tables must be ordered by some
criterion that measures dependence,
and those tables that rep... | null | CC BY-SA 2.5 | null | 2010-09-20T16:15:58.623 | 2010-09-20T16:49:00.773 | 2010-09-20T16:49:00.773 | 25 | 25 | null |
2901 | 2 | null | 2893 | 3 | null | One example of use (interpretation is a better qualifier) of a higher moment: the fifth moment of a univariate distribution measures the asymmetry of its tails.
| null | CC BY-SA 2.5 | null | 2010-09-20T16:42:10.380 | 2010-09-20T20:07:31.340 | 2010-09-20T20:07:31.340 | 603 | 603 | null |
2903 | 2 | null | 2730 | 7 | null | Gelman has a good discussion paper on [ANOVA](http://projecteuclid.org/euclid.aos/1112967698)
Analysis of variance—why it is more important than ever
| null | CC BY-SA 2.5 | null | 2010-09-20T16:54:56.517 | 2010-09-20T16:54:56.517 | null | null | 603 | null |
2904 | 1 | null | null | 7 | 1091 | I am attempting to estimate a model of the following form:
```
W = alphaH * H + alphaM * M + alphaL * L + X * beta
```
where `H, M, L` are indicators for a discrete choice variable, and `beta` is something like 35-dimensional. Because we believe our data/model has endogeneity issues, we have expanded the model to
```
... | How can I work around "lumpiness" in simulated maximum likelihood estimation? | CC BY-SA 2.5 | null | 2010-09-20T17:45:15.683 | 2010-11-16T23:35:41.633 | 2010-11-16T23:35:41.633 | 159 | 53 | [
"matlab",
"stata",
"maximum-likelihood",
"optimization"
] |
2905 | 2 | null | 2892 | 6 | null | I tend to hear that usually 3 largest eigenvalues are the most important, while those close to zero are noise
You can test for that. See the paper linked in [this](https://stats.stackexchange.com/questions/2860/pca-on-out-of-sample-data/2877#2877) post for more detail. Again if your dealing with financial times series ... | null | CC BY-SA 2.5 | null | 2010-09-20T18:49:08.317 | 2010-09-21T11:59:13.977 | 2017-04-13T12:44:46.433 | -1 | 603 | null |
2906 | 1 | 2908 | null | 20 | 1181 | Nassim Taleb, of [Black Swan](http://rads.stackoverflow.com/amzn/click/081297381X) fame (or infamy), has elaborated on the concept and developed what he calls ["a map of the limits of Statistics"](http://www.edge.org/3rd_culture/taleb08/taleb08_index.html). His basic argument is that there is one kind of decision probl... | What is the community's take on the Fourth Quadrant? | CC BY-SA 2.5 | null | 2010-09-20T18:57:24.617 | 2010-09-20T19:13:08.843 | null | null | 666 | [
"distributions",
"modeling",
"random-variable"
] |
2907 | 2 | null | 2686 | 1 | null | I would start with robust time series [filters](http://cran.r-project.org/web/packages/robfilter/index.html) (i.e. time varying medians) because these are more simple and intuitive.
Basically, the robust time filter is to time series smoothers what the median is to the mean; a summary measures (in this case a time vary... | null | CC BY-SA 2.5 | null | 2010-09-20T19:11:45.167 | 2010-09-22T12:44:41.213 | 2010-09-22T12:44:41.213 | 603 | 603 | null |
2908 | 2 | null | 2906 | 28 | null | I was at a meeting of the ASA (American Statistical Association) a couple years ago where Taleb talked about his "fourth quadrant" and it seemed his remarks were well received. Taleb was much more careful in his language when addressing an auditorium of statisticians than he has been in his popular writing.
Some sta... | null | CC BY-SA 2.5 | null | 2010-09-20T19:13:08.843 | 2010-09-20T19:13:08.843 | null | null | 319 | null |
2909 | 1 | 4033 | null | 9 | 1133 | I am interested in the distribution of the maximum drawdown of a random walk: Let $X_0 = 0, X_{i+1} = X_i + Y_{i+1}$ where $Y_i \sim \mathcal{N}(\mu,1)$. The maximum drawdown after $n$ periods is $\max_{0 \le i \le j \le n} (X_i - X_j)$. A paper by [Magdon-Ismail et. al.](http://www.alumni.caltech.edu/~amir/drawdown-jr... | Computing the cumulative distribution of max drawdown of random walk with drift | CC BY-SA 2.5 | null | 2010-09-20T19:59:31.487 | 2018-08-27T16:10:00.043 | 2018-08-27T16:10:00.043 | 11887 | 795 | [
"distributions",
"cumulative-distribution-function",
"finance",
"random-walk"
] |
2910 | 1 | 3191 | null | 92 | 23330 | We often hear of project management and design patterns in computer science, but less frequently in statistical analysis. However, it seems that a decisive step toward designing an effective and durable statistical project is to keep things organized.
I often advocate the use of R and a consistent organization of file... | How to efficiently manage a statistical analysis project? | CC BY-SA 2.5 | null | 2010-09-20T20:39:08.183 | 2018-06-09T04:04:28.840 | 2016-08-10T15:26:11.967 | 7290 | 930 | [
"project-management"
] |
2911 | 2 | null | 2910 | 21 | null | This doesn't specifically provide an answer, but you may want to look at these related stackoverflow questions:
- "Workflow for statistical analysis and report writing"
- "Organizing R Source Code"
- "How to organize large R programs?"
- "R and version control for the solo data analyst"
- "How does software devel... | null | CC BY-SA 2.5 | null | 2010-09-20T20:42:21.877 | 2010-09-25T10:59:17.233 | 2017-05-23T12:39:26.167 | -1 | 5 | null |
2912 | 2 | null | 2892 | 4 | null | One way I have studied this problem in the past is to construct the 'eigenportfolios' of the correlation matrix. That is, take the eigenvector associated with the $k$th largest eigenvalue of the correlation matrix and scale it to a gross leverage of 1 (i.e. make the absolute sum of the vector equal to one). Then see if... | null | CC BY-SA 2.5 | null | 2010-09-20T21:27:28.550 | 2010-09-20T21:27:28.550 | null | null | 795 | null |
2913 | 2 | null | 2860 | 2 | null | What computational savings? The PCA computation is based on the covariance (or correlation) matrix, whose size depends on the number of variables, not the number of data points. The calculation of a covariance matrix is fast. Even if you were doing PCA repeatedly (as part of a simulation, for instance), reducing fro... | null | CC BY-SA 2.5 | null | 2010-09-20T21:29:31.903 | 2010-09-20T21:29:31.903 | null | null | 919 | null |
2914 | 1 | 2931 | null | 14 | 23534 | When you are the one doing the work, being aware of what you are doing you develop a sense of when you have over-fit the model. For one thing, you can track the trend or deterioration in the Adjusted R Square of the model. You can also track a similar deterioration in the p values of the regression coefficients of th... | How to detect when a regression model is over-fit? | CC BY-SA 2.5 | null | 2010-09-20T21:35:58.207 | 2021-11-19T14:13:26.137 | 2017-08-15T21:41:44.853 | 12359 | 1329 | [
"regression",
"multivariate-analysis",
"overfitting"
] |
2915 | 1 | 2928 | null | 4 | 276 | I am talking about the regression method that measures the impact of several layers of independent variables upon a dependent variable.
| What is a good internet based source of information on Hierarchical Modeling? | CC BY-SA 2.5 | null | 2010-09-20T22:16:05.190 | 2010-09-21T11:24:20.990 | 2010-09-21T11:24:20.990 | 183 | 1329 | [
"modeling",
"regression",
"multilevel-analysis"
] |
2916 | 2 | null | 2892 | 14 | null | Eigenvalues give magnitudes of principle components of data spread.
[](https://i.stack.imgur.com/PznUT.png)
(source: [yaroslavvb.com](http://yaroslavvb.com/upload/eigenvalues.png))
First dataset was generated from Gaussian with covariance matrix $\left(\matrix{3&0\\\\0&1}\right)$ second dataset is the first dataset ro... | null | CC BY-SA 4.0 | null | 2010-09-20T23:05:48.593 | 2019-02-17T00:32:01.113 | 2019-02-17T00:32:01.113 | 79696 | 511 | null |
2917 | 1 | null | null | 11 | 3365 |
## Background
I am conducting a meta-analysis that includes previously published data. Often, differences between treatments are reported with P-values, least significant differences (LSD), and other statistics but provide no direct estimate of the variance.
In the context of the model that I am using, an overestima... | Are these formulas for transforming P, LSD, MSD, HSD, CI, to SE as an exact or inflated/conservative estimate of $\hat{\sigma}$ correct? | CC BY-SA 2.5 | null | 2010-09-20T23:14:27.380 | 2011-03-17T02:47:49.370 | 2011-03-17T02:46:32.257 | 795 | 1381 | [
"multiple-comparisons",
"variance",
"data-transformation",
"meta-analysis"
] |
2918 | 1 | null | null | 4 | 1669 | Are Lorenz curves and QQ-plots the same? If not, where are the differences? I read about both of them and they appear to be two terms for the same type of plot / statistical technique to compare distributions. I was not able to find any confirmatory source for this. Perhaps you know?
| Is Lorenz curve the same as QQ-plot? | CC BY-SA 3.0 | null | 2010-09-20T23:22:35.163 | 2014-11-20T01:17:39.007 | 2014-11-20T01:17:39.007 | 805 | 608 | [
"data-visualization",
"qq-plot",
"lorenz-curve"
] |
2919 | 2 | null | 2915 | 4 | null | I warmly recommend Doug Bate's [book](http://lme4.r-forge.r-project.org/book/)
| null | CC BY-SA 2.5 | null | 2010-09-20T23:37:22.590 | 2010-09-20T23:37:22.590 | null | null | 603 | null |
2920 | 2 | null | 2917 | 7 | null | Your LSD equation looks fine. If you want to get back to variance and you have a summary statistic that says something about variability or significance of an effect then you can almost always get back to variance—-you just need to know the formula. For example, in your equation for LSD you want to solve for MSE, MSE... | null | CC BY-SA 2.5 | null | 2010-09-20T23:42:21.657 | 2010-09-20T23:42:21.657 | null | null | 601 | null |
2921 | 2 | null | 2915 | 7 | null | [The Centre for Multilevel Modelling](http://www.cmm.bristol.ac.uk/learning-training/index.shtml) has free online tutorials for multi-level modeling, and they have software tutorials for fitting models in both their MLwiN software and STATA.
You will probably want to check out all the questions with the [multilevel ana... | null | CC BY-SA 2.5 | null | 2010-09-20T23:52:04.230 | 2010-09-21T02:52:02.937 | 2017-04-13T12:44:33.310 | -1 | 1036 | null |
2922 | 2 | null | 2904 | 2 | null | Your likelihood function is non-concave (i.e. the Hessian matrix of your likelihood function is not SDN). From this it follows that
- You will only find a local maximae to your likelihood function (no garantuee of global optimality)
- This maxima will always depend on your choice of starting point.
- Your maximizati... | null | CC BY-SA 2.5 | null | 2010-09-21T00:04:45.017 | 2010-09-22T22:33:24.393 | 2010-09-22T22:33:24.393 | 603 | 603 | null |
2924 | 2 | null | 2904 | 3 | null | It sounds like you need to use a more robust optimization algorithm that can handle local minima. Particle swarm methods work quite well in this case. Or you could try other evolutionary optimization methods or simulated annealing.
| null | CC BY-SA 2.5 | null | 2010-09-21T00:42:04.910 | 2010-09-21T00:42:04.910 | null | null | 159 | null |
2925 | 1 | 2963 | null | 6 | 791 | Suppose that we want to generate a draw from the following distribution:
$P(X=0) = 0.5$
$P(X=1) = 0.5$
There are two constraints though:
(a) The draw has to be on the basis of an external event.
(b) Related to (a), the draw must be verifiable by a third party. In other words, a third party should be able to verify that... | Is there a verifiable way to generate discrete random variables on the basis of an external event? | CC BY-SA 2.5 | null | 2010-09-21T00:47:15.803 | 2020-06-29T21:36:10.710 | null | null | null | [
"random-variable"
] |
2926 | 2 | null | 305 | 4 | null | Two reasons I can think of:
- Regular Student's T is pretty robust to heteroscedasticity if the sample sizes are equal.
- If you believe strongly a priori that the data is homoscedastic, then you lose nothing and might gain a small amount of power by using Studen'ts T instead of Welch's T.
One reason that I would... | null | CC BY-SA 2.5 | null | 2010-09-21T01:36:24.877 | 2010-09-21T01:36:24.877 | null | null | 1347 | null |
2927 | 2 | null | 2914 | 7 | null | When I'm fitting a model myself I generally use information criteria during the fitting process, such as [AIC](http://en.wikipedia.org/wiki/Akaike_information_criterion) or [BIC](http://en.wikipedia.org/wiki/Bayesian_information_criterion), or alternatively [Likelihood-ratio tests](http://en.wikipedia.org/wiki/Likeliho... | null | CC BY-SA 2.5 | null | 2010-09-21T02:14:36.227 | 2010-09-21T02:14:36.227 | null | null | 521 | null |
2928 | 2 | null | 2915 | 6 | null | UCLA has some good resources:
- Papers on multilevel modelling
- Textbook examples (see multilevel modelling)
- A free textbook on multilevel modelling by Harvey Goldstein
- and more...
| null | CC BY-SA 2.5 | null | 2010-09-21T02:25:20.493 | 2010-09-21T02:25:20.493 | null | null | 183 | null |
2929 | 2 | null | 2918 | 11 | null | The Lorenz curve is just a cumulative distribution function for a random variable bounded between 0 and 1, e.g., a proportion. In economics, the Lorenz curve asks, "what fraction of income is earned by the lowest x% of earners?" Typically, it is compared to the uniform distribution over [0,1], a distribution that would... | null | CC BY-SA 2.5 | null | 2010-09-21T02:46:15.140 | 2010-09-21T02:46:15.140 | null | null | 401 | null |
2930 | 2 | null | 2910 | 4 | null | [van Belle](http://rads.stackoverflow.com/amzn/click/0470144483) is the source for the rules of successful statistical projects.
| null | CC BY-SA 2.5 | null | 2010-09-21T03:00:47.613 | 2010-09-21T03:00:47.613 | null | null | 666 | null |
2931 | 2 | null | 2914 | 17 | null | Cross validation is a fairly common way to detect overfitting, while regularization is a technique to prevent it. For a quick take, I'd recommend Andrew Moore's tutorial slides on the use of [cross-validation](https://www.cs.cmu.edu/%7E./awm/tutorials/overfit.html) ([mirror](https://web.archive.org/web/20170815214245/... | null | CC BY-SA 4.0 | null | 2010-09-21T03:32:23.540 | 2021-11-19T14:13:26.137 | 2021-11-19T14:13:26.137 | 322742 | 251 | null |
2932 | 1 | null | null | 6 | 765 | Does the use of metric spaces to describe the support of a random variable provide any greater illumination? I ask this after reading about how metrics spaces have been used to unify the mathematical measure theoretic nature of probability and the physical intuition that most associate with probability. You can read my... | Metric spaces and the support of a random variable | CC BY-SA 2.5 | null | 2010-09-21T03:38:50.050 | 2012-01-08T17:18:07.957 | 2010-09-24T14:00:05.347 | 930 | null | [
"random-variable"
] |
2934 | 1 | null | null | 4 | 852 | I have distributional data which I represent as a density. The data represents frequencies of user activities on a computer screen (e.g. amount of clicks on the y or x-axis of that screen but also other activities that can be related to coordinates and can therefore be binned by those coordinates (e.g. 5 pixels bins)).... | Using Lorenz curve / Gini coefficient for (non-ecomoical) distribution data | CC BY-SA 2.5 | null | 2010-09-21T04:08:56.927 | 2010-09-21T04:57:20.413 | null | null | 608 | [
"distributions"
] |
2935 | 2 | null | 1735 | 5 | null | Here is my suggestion. Rerun your model(s) using one single regression. And, the Summer/Winter variable would be simply a single dummy variable (1,0). This way you would have a coefficient for Summer to differentiate it from Winter. And, the regression coefficients for your three other variables would be consistent... | null | CC BY-SA 2.5 | null | 2010-09-21T04:29:35.863 | 2010-09-21T04:29:35.863 | null | null | 1329 | null |
2936 | 2 | null | 2925 | 3 | null | This reminds me of a question from Algorithms class a long time ago. Let the external event be a (preferrably continuous) random variable $Y$. To generate a value of $X$, take two independent observations of $Y$ and let $X$ be $1$ if the first observation of $Y$ is greater than the second, let it be $0$ if the second i... | null | CC BY-SA 2.5 | null | 2010-09-21T04:48:37.157 | 2010-09-21T16:21:35.873 | 2010-09-21T16:21:35.873 | 795 | 795 | null |
2937 | 2 | null | 2934 | 2 | null | You can use a [2-sample Kolmogorov-Smirnov test](http://en.wikipedia.org/wiki/Kolmogorov_Smirnov_Test#Two-sample_Kolmogorov.E2.80.93Smirnov_test) to compare the two distributions. Other tests for comparing 2-samples are the Anderson-Darling test (although the 2-sample form of this is less frequently used), and the Baum... | null | CC BY-SA 2.5 | null | 2010-09-21T04:57:20.413 | 2010-09-21T04:57:20.413 | null | null | 795 | null |
2938 | 1 | null | null | 12 | 2568 | The qq-plot can be used to visualize how similar two distributions are (e.g. visualizing the similarity of a distribution to a normal distribution, but also to compare two artibrary data distributions). Are there any statistics that generate a more objective, numerical measure that represent their similarity (preferabl... | Quantifying QQ plot | CC BY-SA 3.0 | null | 2010-09-21T05:15:16.743 | 2017-04-13T01:52:10.793 | 2014-11-20T09:49:31.713 | 22047 | 608 | [
"distributions",
"qq-plot"
] |
2939 | 2 | null | 2938 | 8 | null | As I say in response to your comment on your previous question, check out the Kolmogorov-Smirnov test. It uses the maximum absolute distance between two cumulative distribution functions (alternatively conceived as the maximum absolute distance of the curve in the QQ plot from the 45-degree line) as a statistic. The KS... | null | CC BY-SA 2.5 | null | 2010-09-21T05:35:11.600 | 2010-09-21T05:35:11.600 | null | null | 401 | null |
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