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321 | 1 | null | null | 15 | 4663 | There is a variant of boosting called [gentleboost](http://dx.doi.org/10.1214/aos/1016218223). How does gentle boosting differ from the better-known [AdaBoost](http://en.wikipedia.org/wiki/AdaBoost)?
| How does gentle boosting differ from AdaBoost? | CC BY-SA 2.5 | null | 2010-07-20T16:01:25.590 | 2010-09-08T17:30:41.103 | 2010-07-20T19:25:13.293 | 220 | 220 | [
"machine-learning",
"boosting"
] |
322 | 1 | 338 | null | 19 | 4213 | I'm looking for a book or online resource that explains different kinds of entropy such as Sample Entropy and Shannon Entropy and their advantages and disadvantages.
Can someone point me in the right direction?
| Good introduction into different kinds of entropy | CC BY-SA 2.5 | null | 2010-07-20T16:03:40.877 | 2017-09-02T20:13:27.850 | 2017-09-02T20:13:27.850 | 11887 | 3807 | [
"references",
"entropy"
] |
323 | 2 | null | 114 | 22 | null | [Statistical Modeling, Causal Inference, and Social Science](http://www.stat.columbia.edu/~cook/movabletype/mlm/) from Andrew Gelman is a good blog.
| null | CC BY-SA 2.5 | null | 2010-07-20T16:10:16.080 | 2010-07-20T16:10:16.080 | null | null | 3807 | null |
324 | 2 | null | 114 | 9 | null | [Darren Wilkinson's research blog](http://darrenjw.wordpress.com/)
| null | CC BY-SA 2.5 | null | 2010-07-20T16:12:08.700 | 2010-07-20T16:12:08.700 | null | null | 3807 | null |
326 | 2 | null | 114 | 12 | null | [XI'AN'S OG](http://xianblog.wordpress.com/)
| null | CC BY-SA 2.5 | null | 2010-07-20T16:13:03.643 | 2010-07-20T16:13:03.643 | null | null | 3807 | null |
327 | 2 | null | 62 | 3 | null | Malcom Gladewell analyses the problem in the book Outliers by analyzing Hockey Players.
| null | CC BY-SA 2.5 | null | 2010-07-20T16:19:51.750 | 2010-07-20T16:19:51.750 | null | null | 3807 | null |
328 | 1 | 329 | null | 9 | 4012 | I realize that the statistical analysis of financial data is a huge topic, but that is exactly why it is necessary for me to ask my question as I try to break into the world of financial analysis.
As at this point I know next to nothing about the subject, the results of my google searches are overwhelming. Many of th... | Resources for learning about the Statistical Analysis of Financial Data | CC BY-SA 2.5 | null | 2010-07-20T16:27:08.763 | 2012-08-27T15:59:23.840 | 2010-09-17T20:53:00.430 | null | 75 | [
"references",
"finance"
] |
329 | 2 | null | 328 | 14 | null | You might start with this [series of lectures by Robert Shiller at Yale](http://oyc.yale.edu/economics/financial-markets/). He gives a good overview of the field.
My favorite books on the subject:
- I strongly recommend starting with Statistics and Finance, by David Ruppert (the R code for the book is available). Th... | null | CC BY-SA 2.5 | null | 2010-07-20T16:31:26.140 | 2010-07-20T16:49:17.697 | 2010-07-20T16:49:17.697 | 5 | 5 | null |
331 | 2 | null | 305 | 6 | null | Because exact results are preferable to approximations, and avoid odd edge cases where the approximation may lead to a different result than the exact method.
The Welch method isn't a quicker way to do any old t-test, it's a tractable approximation to an otherwise very hard problem: how to construct a t-test under un... | null | CC BY-SA 2.5 | null | 2010-07-20T16:43:42.850 | 2010-07-20T16:43:42.850 | null | null | 61 | null |
333 | 2 | null | 328 | 3 | null | Ed Thorpe started the whole statistical arbitrage thing. He has a website, and some good articles.
[http://edwardothorp.com/](http://edwardothorp.com/)
You should also read Nassim Taleb's "Fooled By Randomness".
Also, go on Google Scholar and read the top articles by Markowitz, Sharpe, Fama, Modigliani. If you don't ha... | null | CC BY-SA 2.5 | null | 2010-07-20T17:17:21.007 | 2010-08-13T18:01:09.700 | 2010-08-13T18:01:09.700 | 74 | 74 | null |
337 | 2 | null | 322 | 2 | null | The entropy is only one (as a concept) -- the amount of information needed to describe some system; there are only many its generalizations. Sample entropy is only some entropy-like descriptor used in heart rate analysis.
| null | CC BY-SA 2.5 | null | 2010-07-20T17:20:41.267 | 2010-07-20T17:36:23.330 | 2010-07-20T17:36:23.330 | null | null | null |
338 | 2 | null | 322 | 10 | null | Cover and Thomas's book [Elements of Information Theory](http://rads.stackoverflow.com/amzn/click/0471062596) is a good source on entropy and its applications, although I don't know that it addresses exactly the issues you have in mind.
| null | CC BY-SA 2.5 | null | 2010-07-20T17:22:01.153 | 2010-09-02T09:52:44.180 | 2010-09-02T09:52:44.180 | 8 | 89 | null |
339 | 2 | null | 26 | 1 | null | If the information required is the distribution of data about the mean, standard deviation comes in handy.
The sum of the difference of each value from the mean is zero (obviously, since the value are evenly spread around the mean), hence we square each difference so as to convert negative values to positive, sum them ... | null | CC BY-SA 2.5 | null | 2010-07-20T17:31:49.313 | 2010-07-20T17:31:49.313 | null | null | 218 | null |
340 | 2 | null | 269 | 9 | null | The population is everything in the group of study. For example, if you are studying the price of Apple's shares, it is the historical, current, and even all future stock prices. Or, if you run an egg factory, it is all the eggs made by the factory.
You don't always have to sample, and do statistical tests. If your pop... | null | CC BY-SA 2.5 | null | 2010-07-20T17:41:00.267 | 2010-07-20T17:41:00.267 | null | null | 74 | null |
341 | 1 | 385 | null | 11 | 25748 | Do you think that unbalanced classes is a big problem for k-nearest neighbor? If so, do you know any smart way to handle this?
| kNN and unbalanced classes | CC BY-SA 2.5 | null | 2010-07-20T18:12:29.550 | 2019-03-03T17:00:40.187 | 2010-07-21T06:50:32.437 | 190 | null | [
"k-nearest-neighbour",
"unbalanced-classes"
] |
342 | 2 | null | 134 | 7 | null | If you're willing to tolerate an approximation, there are other methods. For example, one approximation is a value whose rank is within some (user specified) distance from the true median. For example, the median has (normalized) rank 0.5, and if you specify an error term of 10%, you'd want an answer that has rank betw... | null | CC BY-SA 2.5 | null | 2010-07-20T18:13:44.820 | 2010-07-20T18:13:44.820 | null | null | 139 | null |
343 | 2 | null | 258 | 3 | null | [kNN](http://en.wikipedia.org/wiki/K-nearest_neighbor_algorithm)
| null | CC BY-SA 2.5 | null | 2010-07-20T18:16:17.513 | 2010-07-20T18:16:17.513 | null | null | null | null |
344 | 2 | null | 258 | 3 | null | [Naive Bayes](http://en.wikipedia.org/wiki/Naive_bayes) and [Random Naive Bays](http://en.wikipedia.org/wiki/Random_naive_Bayes)
| null | CC BY-SA 2.5 | null | 2010-07-20T18:17:25.903 | 2010-07-20T18:17:25.903 | null | null | null | null |
345 | 2 | null | 328 | 1 | null | Also good is "Statistical Analysis of Financial Data in S-PLUS" by Rene A. Carmona
| null | CC BY-SA 2.5 | null | 2010-07-20T19:08:50.867 | 2010-07-20T19:08:50.867 | null | null | 247 | null |
346 | 1 | 428 | null | 57 | 30622 | I'm looking for a good algorithm (meaning minimal computation, minimal storage requirements) to estimate the median of a data set that is too large to store, such that each value can only be read once (unless you explicitly store that value). There are no bounds on the data that can be assumed.
Approximations are fine,... | What is a good algorithm for estimating the median of a huge read-once data set? | CC BY-SA 2.5 | null | 2010-07-20T19:21:16.220 | 2020-10-30T01:01:30.200 | 2020-05-25T15:20:58.260 | 1352 | 247 | [
"algorithms",
"median",
"large-data",
"online-algorithms"
] |
347 | 2 | null | 75 | 2 | null | I found this rather helpful: [http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf](http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf)
| null | CC BY-SA 2.5 | null | 2010-07-20T19:50:57.100 | 2010-07-20T19:50:57.100 | null | null | 15 | null |
349 | 2 | null | 346 | 14 | null | How about something like a binning procedure? Assume (for illustration purposes) that you know that the values are between 1 and 1 million. Set up N bins, of size S. So if S=10000, you'd have 100 bins, corresponding to values [1:10000, 10001:20000, ... , 990001:1000000]
Then, step through the values. Instead of stor... | null | CC BY-SA 2.5 | null | 2010-07-20T19:59:33.833 | 2010-07-20T22:40:50.903 | 2010-07-20T22:40:50.903 | 54 | 54 | null |
351 | 2 | null | 7 | 4 | null | [Timetric](https://web.archive.org/web/20100109022706/http://timetric.com/) provides a web interface to data and provide a list of the [publicly available data sets](https://web.archive.org/web/20100704114934/http://timetric.com/dataset/) they use.
| null | CC BY-SA 4.0 | null | 2010-07-20T21:05:35.517 | 2022-11-30T05:35:00.977 | 2022-11-30T05:35:00.977 | 362671 | 16 | null |
352 | 2 | null | 346 | 3 | null | I've never had to do this, so this is just a suggestion.
I see two (other) possibilities.
Half data
- Load in half the data and sort
- Next read in the remaining values and compare against the your sorted list.
If the new value is larger, discard it.
else put the value in the sorted list and removing the largest v... | null | CC BY-SA 2.5 | null | 2010-07-20T21:18:45.380 | 2010-07-21T15:29:25.620 | 2010-07-21T15:29:25.620 | 8 | 8 | null |
353 | 2 | null | 205 | 14 | null | Fisher's scoring is just a version of Newton's method that happens to be identified with GLMs, there's nothing particularly special about it, other than the fact that the Fisher's information matrix happens to be rather easy to find for random variables in the exponential family. It also ties in to a lot of other math... | null | CC BY-SA 2.5 | null | 2010-07-20T22:11:54.673 | 2010-07-20T22:11:54.673 | null | null | 61 | null |
354 | 1 | 176336 | null | 14 | 1012 | Why do we seek to minimize `x^2` instead of minimizing `|x|^1.95` or `|x|^2.05`.
Are there reasons why the number should be exactly two or is it simply a convention that has the advantage of simplifying the math?
| Bias towards natural numbers in the case of least squares | CC BY-SA 2.5 | null | 2010-07-20T22:26:26.083 | 2015-10-10T13:35:27.460 | 2010-11-28T12:04:24.103 | 930 | 3807 | [
"standard-deviation",
"least-squares"
] |
355 | 2 | null | 328 | 1 | null | Check out [Wilmott.com](http://wilmott.com/) as well. It's oriented toward more advanced practitioners, but if I had to choose one person from whom to learn financial math, it would be Paul Wilmott. Brilliant but grounded.
| null | CC BY-SA 2.5 | null | 2010-07-20T22:27:42.633 | 2010-07-20T22:27:42.633 | null | null | 158 | null |
356 | 2 | null | 288 | 3 | null | To fit the model you can use [JAGS](http://www-fis.iarc.fr/~martyn/software/jags/) or [Winbugs](http://www.mrc-bsu.cam.ac.uk/bugs/). In fact if you look at the week 3 of the lecture notes at Paul Hewson's [webpage](http://users.aims.ac.za/~paulhewson/), the rats JAGS example is a beta binomial model. He puts gamma prio... | null | CC BY-SA 2.5 | null | 2010-07-20T22:31:45.140 | 2010-07-20T22:31:45.140 | null | null | 8 | null |
357 | 2 | null | 2 | 6 | null | You can't know whether there normality and that's why you have to make an assumption that's there.
You can only prove the absence of normality with statistic tests.
Even worse, when you work with real world data it's almost certain that there isn't true normality in your data.
That means that your statistical test is a... | null | CC BY-SA 3.0 | null | 2010-07-20T23:07:48.713 | 2011-10-21T19:44:18.317 | 2011-10-21T19:44:18.317 | 3807 | 3807 | null |
358 | 2 | null | 354 | 8 | null | We try to minimize the variance that is left within descriptors. Why variance? Read [this question](https://stats.stackexchange.com/questions/118/standard-deviation-why-square-the-difference-instead-of-taking-the-absolute-val); this also comes together with the (mostly silent) assumption that errors are normally distri... | null | CC BY-SA 2.5 | null | 2010-07-20T23:21:05.400 | 2010-07-21T09:31:29.867 | 2017-04-13T12:44:41.607 | -1 | null | null |
359 | 1 | 457 | null | 11 | 1448 | The Wald, Likelihood Ratio and Lagrange Multiplier tests in the context of maximum likelihood estimation are asymptotically equivalent. However, for small samples, they tend to diverge quite a bit, and in some cases they result in different conclusions.
How can they be ranked according to how likely they are to reject ... | The trinity of tests in maximum likelihood: what to do when faced with contradicting conclusions? | CC BY-SA 2.5 | null | 2010-07-20T23:28:49.693 | 2010-09-20T02:40:27.090 | null | null | 90 | [
"hypothesis-testing",
"maximum-likelihood"
] |
360 | 2 | null | 173 | 6 | null | Does it really need some advanced model? Based on what I know about TB, in case there is no epidemy the infections are stochastic acts and so the count form month N shouldn't be correlated with count from month N-1. (You can check this assumption with autocorrelation). If so, analyzing just the distribution of monthly ... | null | CC BY-SA 2.5 | null | 2010-07-20T23:56:33.933 | 2010-07-20T23:56:33.933 | null | null | null | null |
361 | 2 | null | 258 | 12 | null | [Logistic Regression](http://en.wikipedia.org/wiki/Logistic_regression):
- fast and perform well on most datasets
- almost no parameters to tune
- handles both discrete/continuous features
- model is easily interpretable
- (not really restricted to binary classifications)
| null | CC BY-SA 2.5 | null | 2010-07-21T00:09:09.960 | 2010-07-21T00:09:09.960 | null | null | 170 | null |
362 | 1 | 74954 | null | 41 | 147826 | What is the difference between the Shapiro–Wilk test of normality and the Kolmogorov–Smirnov test of normality? When will results from these two methods differ?
| What is the difference between the Shapiro–Wilk test of normality and the Kolmogorov–Smirnov test of normality? | CC BY-SA 4.0 | null | 2010-07-21T00:24:35.500 | 2022-01-08T20:20:25.947 | 2022-01-08T20:20:25.947 | 155836 | 196 | [
"distributions",
"statistical-significance",
"normality-assumption",
"kolmogorov-smirnov-test"
] |
363 | 1 | null | null | 89 | 16694 | If you could go back in time and tell yourself to read a specific book at the beginning of your career as a statistician, which book would it be?
| What is the single most influential book every statistician should read? | CC BY-SA 2.5 | null | 2010-07-21T00:44:08.597 | 2021-03-11T13:59:49.813 | null | null | 74 | [
"references"
] |
365 | 2 | null | 257 | 5 | null | Another option is [Gnuplot](http://www.gnuplot.info/)
| null | CC BY-SA 2.5 | null | 2010-07-21T01:04:08.710 | 2010-07-21T01:04:08.710 | null | null | 226 | null |
366 | 2 | null | 175 | 1 | null | For a linear regression you could use a repeated median straight line fit.
| null | CC BY-SA 2.5 | null | 2010-07-21T01:23:00.817 | 2010-07-21T01:23:00.817 | null | null | 226 | null |
367 | 2 | null | 363 | 28 | null | I am no statistician, and I haven't read that much on the topic, but perhaps
[Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century](http://rads.stackoverflow.com/amzn/click/0805071342)
should be mentioned? It is no textbook, but still worth reading.
| null | CC BY-SA 2.5 | null | 2010-07-21T01:35:13.500 | 2010-07-21T01:35:13.500 | null | null | 90 | null |
368 | 2 | null | 212 | 2 | null | Suppose that the text has N words and that you require that an ASR should correctly predict at least 95% of words in the text. You currently have the observed error rate for the two methods. You can perform two type of tests.
Test 1: Do the ASR models meet your criteria of 95% prediction?
Test 2: Are the two ASR models... | null | CC BY-SA 2.5 | null | 2010-07-21T03:01:00.020 | 2010-07-21T03:01:00.020 | null | null | null | null |
369 | 1 | null | null | 7 | 921 | Say I've got a program that monitors a news feed and as I'm monitoring it I'd like to discover when a bunch of stories come out with a particular keyword in the title. Ideally I want to know when there are an unusual number of stories clustered around one another.
I'm entirely new to statistical analysis and I'm wonder... | Working through a clustering problem | CC BY-SA 2.5 | null | 2010-07-21T03:47:17.577 | 2012-05-26T04:00:14.573 | 2010-09-17T20:53:12.380 | null | 191 | [
"clustering"
] |
370 | 2 | null | 363 | 40 | null | Here are two to put on the list:
[Tufte. The visual display of quantitative information](http://rads.stackoverflow.com/amzn/click/096139210X)
[Tukey. Exploratory data analysis](http://rads.stackoverflow.com/amzn/click/0201076160)
| null | CC BY-SA 2.5 | null | 2010-07-21T03:48:55.563 | 2010-07-21T03:48:55.563 | null | null | 159 | null |
371 | 2 | null | 363 | 22 | null | [Probability Theory: The Logic of Science](http://rads.stackoverflow.com/amzn/click/0521592712)
| null | CC BY-SA 2.5 | null | 2010-07-21T04:19:00.347 | 2010-07-21T04:19:00.347 | null | null | 34 | null |
372 | 1 | 381 | null | 4 | 1680 | What topics in statistics are most useful/relevant to data mining?
| What are the key statistical concepts that relate to data mining? | CC BY-SA 2.5 | null | 2010-07-21T04:26:07.550 | 2010-09-13T13:16:33.200 | 2010-08-12T13:24:12.943 | 509 | 252 | [
"probability",
"data-mining",
"cart"
] |
373 | 1 | 378 | null | 41 | 6973 | From Wikipedia :
>
Suppose you're on a game show, and
you're given the choice of three
doors: Behind one door is a car;
behind the others, goats. You pick a
door, say No. 1, and the host, who
knows what's behind the doors, opens
another door, say No. 3, which has a
goat. He then says to you, "Do you
wa... | The Monty Hall Problem - where does our intuition fail us? | CC BY-SA 2.5 | null | 2010-07-21T04:30:50.663 | 2022-10-13T18:56:58.043 | 2016-12-22T02:30:47.107 | 12359 | 252 | [
"probability",
"intuition",
"puzzle"
] |
374 | 1 | 379 | null | 9 | 1793 | What are pivot tables, and how can they be helpful in analyzing data?
| What are pivot tables, and how can they be helpful in analyzing data? | CC BY-SA 2.5 | null | 2010-07-21T04:32:42.520 | 2015-11-04T05:47:31.513 | 2015-11-04T05:47:31.513 | 805 | 252 | [
"multivariate-analysis",
"pivot-table"
] |
375 | 1 | null | null | 7 | 492 | >
Possible Duplicate:
Testing random variate generation algorithms
What's a good way to test a series of numbers to see if they're random (or at least psuedo-random)? Is there a good statistical measure of randomness that can be used to determine how random a set is?
More importantly, how can one prove a method of ... | Testing (and proving) the randomness of numbers | CC BY-SA 2.5 | 0 | 2010-07-21T04:34:45.700 | 2010-07-26T20:12:15.570 | 2017-04-13T12:44:39.283 | -1 | 252 | [
"random-generation",
"proof",
"randomness"
] |
376 | 2 | null | 354 | 14 | null | There's no reason you couldn't try to minimize norms other than x^2, there have been entire books written on quantile regression, for instance, which is more or less minimizing |x| if you're working with the median. It's just generally harder to do and, depending on the error model, may not give good estimators (depen... | null | CC BY-SA 2.5 | null | 2010-07-21T04:48:50.457 | 2010-07-21T04:48:50.457 | null | null | 61 | null |
378 | 2 | null | 373 | 14 | null | Consider two simple variations of the problem:
- No doors are opened for the contestant. The host offers no help in picking a door. In this case it is obvious that the odds of picking the correct door are 1/3.
- Before the contestant is asked to venture a guess, the host opens a door and reveals a goat. After the ho... | null | CC BY-SA 2.5 | null | 2010-07-21T05:54:25.527 | 2010-07-21T05:54:25.527 | null | null | 68 | null |
379 | 2 | null | 374 | 9 | null | A pivot-table is a tool to dynamically show a slice and group multivariate data in tabular form.
For example, when we have the following data structure
```
Region Year Product Sales
US 2008 Phones 125
EU 2008 Phones 352
US 2008 Mouses 52
EU 2008 Mouses 65
US 2009 Phones 1... | null | CC BY-SA 2.5 | null | 2010-07-21T06:09:43.093 | 2010-07-21T08:00:10.447 | 2017-03-09T17:30:36.053 | -1 | 190 | null |
380 | 2 | null | 30 | 4 | null | You cannot prove, because it is impossible; you can only check if there are no any embarrassing autocorrelations or distribution disturbances, and indeed [Diehard](http://en.wikipedia.org/wiki/Diehard_tests) is a standard for it. This is for statistics/physics, cryptographers will also mainly check (among other things)... | null | CC BY-SA 2.5 | null | 2010-07-21T06:15:36.623 | 2010-07-21T06:15:36.623 | null | null | null | null |
381 | 2 | null | 372 | 7 | null | Understanding multivariate normal distribution [http://en.wikipedia.org/wiki/Multivariate_normal_distribution](http://en.wikipedia.org/wiki/Multivariate_normal_distribution) is important.
The concept of correlation and more generally (non linear) dependence is important.
Concentration of measure, asymptotic normality... | null | CC BY-SA 2.5 | null | 2010-07-21T06:22:51.820 | 2010-07-21T06:22:51.820 | null | null | 223 | null |
382 | 2 | null | 124 | 4 | null | Firstly I can recommend you the book [Foundations of statistical natural language processing](http://nlp.stanford.edu/fsnlp/) by Manning and Schütze.
The methods I would use are word-frequency distributions and ngram language models. The first works very well when you want to classify on topic and your topics are speci... | null | CC BY-SA 2.5 | null | 2010-07-21T06:28:23.900 | 2010-07-21T06:28:23.900 | null | null | 190 | null |
383 | 2 | null | 4 | 5 | null | You might be interested in applying relative distribution methods. Call one group the reference group, and the other the comparison group. In a way similar to constructing a probability-probability plot, you can construct a relative CDF/PDF, which is a ratio of the densities. This relative density can be used for in... | null | CC BY-SA 2.5 | null | 2010-07-21T06:28:43.477 | 2010-07-21T06:28:43.477 | null | null | 251 | null |
384 | 2 | null | 369 | 1 | null | I would start with a frequency distribution. Collect for a big corpus the word-frequencies and select smartly the words that are keywords (not misspellings, with a very low frequency, and not stop words like "and", "or")
Then when you have a number of new feeds, compare their distribution with the distribution that you... | null | CC BY-SA 2.5 | null | 2010-07-21T06:33:36.307 | 2010-07-21T06:33:36.307 | null | null | 190 | null |
385 | 2 | null | 341 | 0 | null | In principal, unbalanced classes are not a problem at all for the k-nearest neighbor algorithm.
Because the algorithm is not influenced in any way by the size of the class, it will not favor any on the basis of size. Try to run k-means with an obvious outlier and k+1 and you will see that most of the time the outlier ... | null | CC BY-SA 3.0 | null | 2010-07-21T06:39:38.230 | 2015-05-05T13:48:09.747 | 2015-05-05T13:48:09.747 | 7365 | 190 | null |
386 | 2 | null | 213 | 14 | null | I would do some sort of "leave one out testing algorithm" (n is the number of data):
for i=1 to n
- compute a density estimation of the data set obtained by throwing $X_i$ away. (This density estimate should be done with some assumption if the dimension is high, for example, a gaussian assumption for which the density... | null | CC BY-SA 3.0 | null | 2010-07-21T06:46:11.897 | 2011-06-14T18:26:43.130 | 2011-06-14T18:26:43.130 | 223 | 223 | null |
387 | 2 | null | 7 | 49 | null | The following list contains many data sets you may be interested:
- America's Best Colleges - U.S. News & World Reports
- American FactFinder
- The Baseball Archive
- The Bureau of Justice Statistics
- The Bureau of Labor Statistics
- The Bureau of Transportation Statistics
- The Census Bureau
- Data and Story ... | null | CC BY-SA 4.0 | null | 2010-07-21T07:04:26.103 | 2022-11-22T02:50:37.240 | 2022-11-22T02:50:37.240 | 362671 | 69 | null |
388 | 2 | null | 363 | 6 | null | On the math/foundations side: Harald Cramér's [Mathematical Methods of Statistics](http://rads.stackoverflow.com/amzn/click/0691005478).
| null | CC BY-SA 2.5 | null | 2010-07-21T07:15:54.857 | 2010-07-21T07:15:54.857 | null | null | 251 | null |
389 | 2 | null | 175 | 22 | null | I do think there is something to be said for just excluding the outliers. A regression line is supposed to summarise the data. Because of leverage you can have a situation where 1% of your data points affects the slope by 50%.
It's only dangerous from a moral and scientific point of view if you don't tell anybody that ... | null | CC BY-SA 2.5 | null | 2010-07-21T07:51:34.243 | 2010-07-21T07:51:34.243 | null | null | 199 | null |
390 | 2 | null | 363 | 4 | null | [Fooled By Randomness](http://rads.stackoverflow.com/amzn/click/1587990717) by Taleb
Taleb is a professor at Columbia and an options trader. He made about $800 million dollars in 2008 betting against the market. He also wrote Black Swan. He discusses the absurdity of using the normal distribution to model markets, and ... | null | CC BY-SA 2.5 | null | 2010-07-21T08:01:54.403 | 2010-09-09T20:46:31.427 | 2010-09-09T20:46:31.427 | 74 | 74 | null |
392 | 2 | null | 257 | 6 | null | Take a look at the sample galleries for three popular visualization libraries:
- matplotlib gallery (Python)
- R graph gallery (R) -- (also see ggplot2, scroll down to reference)
- prefuse visualization gallery (Java)
For the first two, you can even view the associated source code -- the simple stuff is simple, no... | null | CC BY-SA 2.5 | null | 2010-07-21T08:19:36.577 | 2010-07-21T08:19:36.577 | null | null | 251 | null |
393 | 2 | null | 363 | 36 | null | The Elements of Statistical Learning from Hastie, Tibshirani and Friedman [http://www-stat.stanford.edu/~tibs/ElemStatLearn/](http://www-stat.stanford.edu/~tibs/ElemStatLearn/) should be in any statistician's library !
| null | CC BY-SA 4.0 | null | 2010-07-21T09:02:11.717 | 2019-02-08T00:10:58.393 | 2019-02-08T00:10:58.393 | 40067 | 223 | null |
394 | 2 | null | 354 | 1 | null | My understanding is that because we are trying to minimise errors, we need to find a way of not getting ourselves in a situation where the sum of the negative difference in errors is equal to the sum of the positive difference in errors but we haven't found a good fit. We do this by squaring the sum of the difference i... | null | CC BY-SA 3.0 | null | 2010-07-21T09:53:40.083 | 2013-01-09T21:19:25.140 | 2013-01-09T21:19:25.140 | 17230 | 210 | null |
395 | 1 | null | null | 5 | 230 | I have a data set where a series of measurements are being taken each week. In general the data set shows a +/- 1mm change each week with a mean measurement staying at about 0mm. In plotting the data this week it appears that some noticeable movement has occurred at two points and looking back at the data set, it is al... | How to tell if something happened in a data set which monitors a value over time | CC BY-SA 2.5 | null | 2010-07-21T10:13:25.813 | 2011-02-09T11:30:29.170 | 2011-02-09T11:30:29.170 | 556 | 210 | [
"variance",
"monitoring"
] |
396 | 1 | 399 | null | 45 | 6608 | I usually make my own idiosyncratic choices when preparing plots. However, I wonder if there are any best practices for generating plots.
Note: [Rob's comment](https://stats.stackexchange.com/questions/257/what-is-the-easiest-way-to-create-publication-quality-plots-under-linux#comment152_261) to an answer to this [que... | What best practices should I follow when preparing plots? | CC BY-SA 3.0 | null | 2010-07-21T11:00:44.557 | 2022-11-23T09:56:13.210 | 2017-04-13T12:44:53.513 | -1 | null | [
"data-visualization",
"references"
] |
397 | 2 | null | 30 | 10 | null | Just to add a bit to honk's answer, the [Diehard Test Suite](http://en.wikipedia.org/wiki/Diehard_tests) (developed by George Marsaglia) are the standard tests for PRNG.
There's a nice [Diehard C library](https://webhome.phy.duke.edu/%7Ergb/General/dieharder.php) that gives you access to these tests. As well as the sta... | null | CC BY-SA 4.0 | null | 2010-07-21T11:11:47.037 | 2022-12-05T08:26:28.510 | 2022-12-05T08:26:28.510 | 362671 | 8 | null |
398 | 2 | null | 396 | 15 | null | We could stay here all day denoting best practices, but you should start by reading Tufte. My primary recommendation:
Keep it simple.
Often people try to load up their charts with information. But you should really just have one main idea that you're trying to convey and if someone doesn't get your message almost imm... | null | CC BY-SA 2.5 | null | 2010-07-21T11:16:55.077 | 2010-07-21T11:16:55.077 | null | null | 5 | null |
399 | 2 | null | 396 | 26 | null | The Tufte principles are very good practices when preparing plots. See also his book [Beautiful Evidence](http://rads.stackoverflow.com/amzn/click/0961392177)
The principles include:
- Keep a high data-ink ratio
- Remove chart junk
- Give graphical element multiple functions
- Keep in mind the data density
The te... | null | CC BY-SA 2.5 | null | 2010-07-21T11:18:56.323 | 2010-07-21T11:18:56.323 | null | null | 190 | null |
400 | 2 | null | 396 | 13 | null | One rule of thumb that I don't always follow but which is on occasion useful is to take into account that it is likely that your plot will at some point in its future be
- sent by fax,
- photocopied, and/or
- reproduced in black-and-white.
You need to try and make your plots clear enough that even if they are impr... | null | CC BY-SA 3.0 | null | 2010-07-21T11:20:45.167 | 2016-09-17T13:44:39.513 | 2016-09-17T13:44:39.513 | 22047 | 210 | null |
401 | 2 | null | 369 | 2 | null | This problem you are asking about is known as text mining!
There are a few things you need to consider. For example in your question you mentioned using keywords in titles. One may ask "why not the text in the article rather than just the title?" which brings me to the first consideration: What data do you limit yourse... | null | CC BY-SA 3.0 | null | 2010-07-21T12:22:21.570 | 2012-05-26T04:00:14.573 | 2012-05-26T04:00:14.573 | 5505 | 256 | null |
402 | 2 | null | 173 | 4 | null | You might consider applying a [Tukey Control chart](http://gunston.gmu.edu/708/frTukey.asp) to the data.
| null | CC BY-SA 2.5 | null | 2010-07-21T12:30:43.210 | 2010-07-21T12:30:43.210 | null | null | 226 | null |
403 | 2 | null | 192 | 1 | null | I must agree.. there is no single best analysis!
not just in cross tabulations or analysis of categorical data but in any data analysis... and thank god for that!
if there was just a single best way to address these analyses well many of us would not have a job to start with... not to mention the loss of the thrill of ... | null | CC BY-SA 2.5 | null | 2010-07-21T12:33:43.903 | 2010-07-21T12:33:43.903 | null | null | 256 | null |
404 | 2 | null | 173 | 7 | null | You might want to have a look at [strucchange](http://cran.r-project.org/web/packages/strucchange/index.html):
>
Testing, monitoring and dating structural changes in (linear) regression models. strucchange features tests/methods from the generalized fluctuation test framework as well as from the F test (Chow test) fr... | null | CC BY-SA 2.5 | null | 2010-07-21T12:37:31.977 | 2010-07-21T12:37:31.977 | null | null | 46 | null |
405 | 2 | null | 395 | 1 | null | What kind of movement are we talking about?
You could of course fit a distribution over your data and see whether the new weeks fit in this distribution or are in the tail of it (which means it is likely something significant, real that you are observing)
However, more information from your side would be helpful. Maybe... | null | CC BY-SA 2.5 | null | 2010-07-21T12:38:51.197 | 2010-07-21T12:38:51.197 | null | null | 190 | null |
406 | 2 | null | 6 | 27 | null | I disagree with this question as it suggests that machine learning and statistics are different or conflicting sciences.... when the opposite is true!
machine learning makes extensive use of statistics... a quick survey of any Machine learning or data mining software package will reveal Clustering techniques such as k-... | null | CC BY-SA 2.5 | null | 2010-07-21T12:43:00.080 | 2010-07-21T12:43:00.080 | null | null | 256 | null |
407 | 2 | null | 213 | 1 | null | One of the above answers touched in mahalanobis distances.... perhaps anpther step further and calculating simultaneous confidence intervals would help detect outliers!
| null | CC BY-SA 2.5 | null | 2010-07-21T12:59:00.577 | 2010-07-21T12:59:00.577 | null | null | 256 | null |
408 | 2 | null | 396 | 8 | null | In addition to conveying a clear message I always try to remember the plotsmanship:
- font sizes for labels and legends should be big enough, preferably the same font size and font used in the final publication.
- linewidths should be big enough (1 pt lines tend to disappear if plots are shrunk only slightly). I try ... | null | CC BY-SA 3.0 | null | 2010-07-21T13:01:39.883 | 2016-09-17T13:38:21.213 | 2016-09-17T13:38:21.213 | 7482 | 56 | null |
409 | 1 | null | null | 3 | 521 | At the moment I use standard deviation of the mean to estimate uncertainty:
where N is in hundreds and mean is a time series (monthly) mean. I
present it then like this: ![mean plus-minus stdev about th... | How to approximate measurement uncertainty? | CC BY-SA 4.0 | null | 2010-07-21T13:11:33.167 | 2019-01-01T14:07:19.890 | 2019-01-01T14:07:19.890 | 79696 | 219 | [
"time-series",
"standard-deviation",
"mean",
"uncertainty"
] |
410 | 2 | null | 409 | 2 | null | The answer to this question depends a lot on how your measurement uncertainty arises. If it is due to to uncorrelated normally distributed fluctuations in your measurement your measurement outcomes will also be normally distributed.
If this assumption is valid can be hard to prove, but plotting histograms of outcomes o... | null | CC BY-SA 2.5 | null | 2010-07-21T13:20:53.847 | 2010-07-21T13:20:53.847 | null | null | 56 | null |
411 | 1 | null | null | 51 | 15106 | There are many ways to measure how similar two probability distributions are. Among methods which are popular (in different circles) are:
- the Kolmogorov distance: the sup-distance between the distribution functions;
- the Kantorovich-Rubinstein distance: the maximum difference between the expectations w.r.t. the t... | Motivation for Kolmogorov distance between distributions | CC BY-SA 3.0 | null | 2010-07-21T13:39:06.783 | 2022-08-03T22:46:15.427 | 2013-09-04T01:41:58.663 | 29617 | 89 | [
"distributions",
"probability",
"hypothesis-testing",
"mathematical-statistics"
] |
412 | 2 | null | 395 | 5 | null | I think you need look at statistical [control charts](http://en.wikipedia.org/wiki/Control_chart). The most common of which are cusum and Shewhart charts.
Basically, data arrives sequentially and is tested against a number of rules. For example,
- Is the data far away from the cumulative mean - say 3 standard deviatio... | null | CC BY-SA 2.5 | null | 2010-07-21T13:40:02.007 | 2010-07-21T13:40:02.007 | null | null | 8 | null |
413 | 2 | null | 6 | 11 | null | I don't really know what the conceptual/historical difference between machine learning and statistic is but I am sure it is not that obvious... and I am not really interest in knowing if I am a machine learner or a statistician, I think 10 years after Breiman's paper, lots of people are both...
Anyway, I found interes... | null | CC BY-SA 2.5 | null | 2010-07-21T13:48:15.687 | 2010-07-21T13:48:15.687 | null | null | 223 | null |
414 | 1 | 439 | null | 60 | 20615 | What is a good introduction to statistics for a mathematician who is already well-versed in probability? I have two distinct motivations for asking, which may well lead to different suggestions:
- I'd like to better understand the statistics motivation behind many problems considered by probabilists.
- I'd like to k... | Introduction to statistics for mathematicians | CC BY-SA 2.5 | null | 2010-07-21T13:50:08.847 | 2023-02-11T10:15:04.673 | 2010-08-13T17:20:39.927 | 509 | 89 | [
"references"
] |
415 | 2 | null | 414 | 8 | null | I think you should take a look to the similar [post](https://mathoverflow.net/questions/31655/statistics-for-mathematicians/31665#31665) from mathoverflow.
My answer to this post was [Asymptotic Statistics](https://www.cambridge.org/core/books/asymptotic-statistics/A3C7DAD3F7E66A1FA60E9C8FE132EE1D) by Van der Vaart.
| null | CC BY-SA 4.0 | null | 2010-07-21T13:53:13.193 | 2023-02-11T10:11:57.943 | 2023-02-11T10:11:57.943 | 362671 | 223 | null |
416 | 2 | null | 269 | 41 | null | The population is the set of entities under study. For example, the mean height of men. This is a hypothetical population because it includes all men that have lived, are alive and will live in the future. I like this example because it drives home the point that we, as analysts, choose the population that we wish to s... | null | CC BY-SA 2.5 | null | 2010-07-21T14:00:03.147 | 2010-07-21T14:00:03.147 | null | null | 215 | null |
417 | 2 | null | 414 | 15 | null | [Mathematical Methods of Statistics](http://www.powells.com/biblio/61-9780691005478-1), Harald Cramér is really great if you're coming to Statistics from the mathematical side. It's a bit dated, but still relevant for all the basic mathematical statistics.
Two other noteworthy books come to mind for inference and esti... | null | CC BY-SA 2.5 | null | 2010-07-21T14:01:46.887 | 2010-07-21T14:01:46.887 | null | null | 251 | null |
418 | 1 | 113367 | null | 35 | 10303 | Coming from the field of computer vision, I've often used the [RANSAC](http://en.wikipedia.org/wiki/RANSAC) (Random Sample Consensus) method for fitting models to data with lots of outliers.
However, I've never seen it used by statisticians, and I've always been under the impression that it wasn't considered a "statis... | Why isn't RANSAC most widely used in statistics? | CC BY-SA 2.5 | null | 2010-07-21T14:30:42.197 | 2015-05-10T20:52:28.663 | 2010-07-21T17:30:38.037 | null | 77 | [
"outliers",
"bootstrap",
"robust"
] |
419 | 2 | null | 373 | 7 | null | I agree that students find this problem very difficult. The typical response I get is that after you've been shown a goat there's a 50:50 chance of getting the car so why does it matter? Students seem to divorce their first choice from the decision they're now being asked to make i.e. they view these two actions as ind... | null | CC BY-SA 2.5 | null | 2010-07-21T14:43:31.513 | 2010-07-21T14:43:31.513 | null | null | 215 | null |
420 | 2 | null | 373 | 11 | null | I'd modify what Graham Cookson said slightly. I think the really crucial thing that people overlook is not their first choice, but the host's choice, and the assumption that the host made sure not to reveal the car.
In fact, when I discuss this problem in a class, I present it in part as a case study in being clear ... | null | CC BY-SA 2.5 | null | 2010-07-21T14:55:06.430 | 2010-07-21T14:55:06.430 | null | null | 89 | null |
421 | 1 | null | null | 106 | 37759 | What book would you recommend for scientists who are not statisticians?
Clear delivery is most appreciated. As well as the explanation of the appropriate techniques and methods for typical tasks: time series analysis, presentation and aggregation of large data sets.
| What book would you recommend for non-statistician scientists? | CC BY-SA 3.0 | null | 2010-07-21T15:01:21.127 | 2023-04-30T09:27:17.000 | 2017-01-21T09:27:37.137 | 28666 | 219 | [
"references"
] |
422 | 2 | null | 421 | 0 | null | That'll depend very much on their background, but I found ["Statistics in a Nutshell"](http://www.amazon.co.uk/Statistics-Nutshell-Desktop-Reference-OReilly/dp/0596510497) to be pretty good.
| null | CC BY-SA 3.0 | null | 2010-07-21T15:09:11.543 | 2012-08-03T10:07:04.063 | 2012-08-03T10:07:04.063 | null | 247 | null |
423 | 1 | null | null | 377 | 179622 | Data analysis cartoons can be useful for many reasons: they help communicate; they show that quantitative people have a sense of humor too; they can instigate good teaching moments; and they can help us remember important principles and lessons.
[This is one of my favorites:](https://xkcd.com/552/)
![XKCD irony about c... | What is your favorite "data analysis" cartoon? | CC BY-SA 4.0 | null | 2010-07-21T15:13:21.493 | 2022-10-16T03:37:54.007 | 2021-04-27T18:32:58.423 | 919 | 5 | [
"references",
"teaching",
"humor"
] |
424 | 2 | null | 423 | 244 | null | Was XKCD, so time for Dilbert:
Source: [http://dilbert.com/strip/2001-10-25](http://dilbert.com/strip/2001-10-25)
| null | CC BY-SA 3.0 | null | 2010-07-21T15:21:33.883 | 2015-01-28T20:57:36.773 | 2017-03-09T17:30:36.163 | -1 | null | null |
425 | 2 | null | 423 | 180 | null | One of my favorites from [xckd](http://www.xkcd.com):
## Random Number
[](http://xkcd.com/221/)
>
RFC 1149.5 specifies 4 as the standard IEEE-vetted random number.
| null | CC BY-SA 3.0 | null | 2010-07-21T15:23:53.183 | 2017-01-25T13:00:27.543 | 2020-06-11T14:32:37.003 | -1 | 13 | null |
427 | 2 | null | 31 | 50 | null | Before touching this topic, I always make sure that students are happy moving between percentages, decimals, odds and fractions. If they are not completely happy with this then they can get confused very quickly.
I like to explain hypothesis testing for the first time (and therefore p-values and test statistics) throug... | null | CC BY-SA 3.0 | null | 2010-07-21T15:33:11.690 | 2017-04-02T18:42:04.937 | 2017-04-02T18:42:04.937 | 148472 | 215 | null |
428 | 2 | null | 346 | 7 | null | Could you group the data set into much smaller data sets (say 100 or 1000 or 10,000 data points) If you then calculated the median of each of the groups. If you did this with enough data sets you could plot something like the average of the results of each of the smaller sets and this woul, by running enough smaller da... | null | CC BY-SA 2.5 | null | 2010-07-21T15:35:45.560 | 2010-07-21T15:35:45.560 | null | null | 210 | null |
429 | 2 | null | 362 | 27 | null | Briefly stated, the Shapiro-Wilk test is a specific test for normality, whereas the method used by [Kolmogorov-Smirnov test](http://www.itl.nist.gov/div898/handbook/eda/section3/eda35g.htm) is more general, but less powerful (meaning it correctly rejects the null hypothesis of normality less often). Both statistics tak... | null | CC BY-SA 4.0 | null | 2010-07-21T15:36:34.687 | 2019-01-03T01:08:04.550 | 2019-01-03T01:08:04.550 | 79696 | 39 | null |
430 | 2 | null | 373 | 23 | null | I find that people find the solution more intuitive if you change it to 100 doors, close first, second, to 98 doors. Similarly for 50 doors, etc.
| null | CC BY-SA 2.5 | null | 2010-07-21T15:37:17.370 | 2010-07-22T00:37:06.953 | 2010-07-22T00:37:06.953 | 251 | 251 | null |
431 | 2 | null | 363 | 11 | null | I think every statistician should read Stigler's [The History of Statistics: The Measurement of Uncertainty before 1900](http://rads.stackoverflow.com/amzn/click/067440341X)
It is beautifully written, thorough and it isn't a historian's perspective but a mathematician's, hence it doesn't avoid the technical details.
| null | CC BY-SA 2.5 | null | 2010-07-21T15:38:11.677 | 2011-02-20T02:34:07.180 | 2011-02-20T02:34:07.180 | 159 | 215 | null |
432 | 2 | null | 423 | 208 | null | My favourite Dilbert cartoon:
Source: [http://dilbert.com/strip/2008-05-07](http://dilbert.com/strip/2008-05-07)
| null | CC BY-SA 3.0 | null | 2010-07-21T15:38:46.170 | 2015-01-27T20:43:00.943 | 2015-01-27T20:43:00.943 | 8 | 8 | null |
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