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5788 | 1 | 5789 | null | 7 | 4923 | I am attempting to examine the change in slope between a predictor and response over two years. In year 1, it is definitely positive. (Linear regression, the 95% CI of the slope doesn't overlap 0). In year 2, the point estimate of the slope is close to 0 (0.002) and the CI overlaps 0. This is what I would expect if ... | How to tell if the slope of a line is 0 or there is just no relationship? | CC BY-SA 2.5 | null | 2010-12-28T17:00:55.580 | 2010-12-29T09:44:26.790 | 2010-12-29T09:44:26.790 | null | 101 | [
"regression",
"statistical-significance"
] |
5789 | 2 | null | 5788 | 8 | null | Well, your colleague definitely is incorrect, as many standard examples will show. For example, for the data $(x, x(1-x))$ with values of $x$ equal to $0, 1/n, 2/n, \ldots, 1$, the slope is exactly zero but obviously there's a strong (quadratic) relationship between "predictor" ($x$) and "response" ($x(1-x)$). Your c... | null | CC BY-SA 2.5 | null | 2010-12-28T17:54:58.717 | 2010-12-28T17:54:58.717 | null | null | 919 | null |
5790 | 2 | null | 5782 | 42 | null | Update
I've underestimated Taylor expansions. They actually work. I assumed that integral of the remainder term can be unbounded, but with a little work it can be shown that this is not the case.
The Taylor expansion works for functions in bounded closed interval. For random variables with finite variance [Chebyshev i... | null | CC BY-SA 4.0 | null | 2010-12-28T19:23:58.687 | 2020-03-01T13:35:12.273 | 2020-03-01T13:35:12.273 | 5654 | 2116 | null |
5791 | 1 | 5823 | null | 9 | 2964 |
## Background
I have a model with 17 parameters, and I currently use the coefficient of variation ($\text{CV}=\sigma/\mu$) to summarize the prior and posterior distributions of each parameter.
All of the parameters are > 0. I would also like to summarize these pdfs on a normalized scale (in this case standard devia... | Alternatives to using Coefficient of Variation to summarize a set of parameter distributions? | CC BY-SA 2.5 | null | 2010-12-28T19:53:11.963 | 2017-06-12T17:00:41.810 | 2017-06-12T17:00:41.810 | 11887 | 1381 | [
"distributions",
"data-visualization",
"descriptive-statistics",
"winsorizing",
"l-moments"
] |
5792 | 1 | 5793 | null | 9 | 10031 | How can I extract the R-square from a fit [rpart](http://cran.r-project.org/web/packages/rpart/index.html) model?
`rsq.rpart(fit)`
plots the two graphs, but I simply want to extract the R-square value for the full tree.
I assume this is fairly obvious, but numerous searches didn't really lend anything useful. Any... | R-square from rpart model | CC BY-SA 2.5 | null | 2010-12-28T19:56:05.327 | 2010-12-28T20:31:25.117 | 2010-12-28T20:31:25.117 | 930 | 569 | [
"r",
"rpart"
] |
5793 | 2 | null | 5792 | 9 | null | The advantage of R is that most of the time you can easily access the source code. So in your case, start with
```
> rsq.rpart
```
(without parenthesis) to see what the function actually does. The $R^2$ values are obtained as
```
tmp <- printcp(fit)
rsq.val <- 1-tmp[,c(3,4)]
```
where for each row (aka, No. splits)... | null | CC BY-SA 2.5 | null | 2010-12-28T20:28:57.350 | 2010-12-28T20:28:57.350 | null | null | 930 | null |
5795 | 2 | null | 5786 | 1 | null | I guess you know that the kernel for logistic regression is a non parametric one, so first of all you have that restriction.
Regarding the R package the one I know and works pretty well is [np](http://cran.r-project.org/web/packages/np/index.html): Nonparametric kernel smoothing methods for mixed data types
This packag... | null | CC BY-SA 2.5 | null | 2010-12-28T22:01:12.497 | 2010-12-28T22:01:12.497 | null | null | 1808 | null |
5796 | 2 | null | 5786 | 8 | null | Gaussian process classification (using Expectation Propagation) is probably the state-of-the-art in machine learning. There is an excellent [book](http://www.gaussianprocess.org/gpml/chapters/) by Rasmussen and Williams (downloadable for free), the [website](http://www.gaussianprocess.org/gpml/) for which has a very g... | null | CC BY-SA 2.5 | null | 2010-12-28T22:30:00.733 | 2010-12-28T22:30:00.733 | null | null | 887 | null |
5797 | 1 | 5824 | null | 6 | 360 | Given $K$ possible 'treatments' of some kind, and independent observations of some response under those treatments, say $X_{i,k}$ for $i=1,\ldots,n_k$ and $k=1,\ldots,K$, I am faced with the classical data-mining dilemma. The task is to simultaneously:
- Find the treatment, say $k^*$, which maximizes effect, and
- Es... | Is there a bias correction for effect size in a data mining context? | CC BY-SA 2.5 | null | 2010-12-28T22:45:59.357 | 2015-09-22T03:07:38.077 | 2015-09-22T03:07:38.077 | 9007 | 795 | [
"multivariate-analysis",
"data-mining",
"multiple-comparisons",
"unbiased-estimator",
"bias-correction"
] |
5799 | 2 | null | 5750 | 8 | null | Perhaps you could do a preliminary analysis on a random subset of the data to form hypotheses, and then test those few hypotheses of interest using the rest of the data. That way you would not have to correct for nearly as many multiple tests. (I think...)
Of course, if you use such a procedure you will be reducing the... | null | CC BY-SA 2.5 | null | 2010-12-29T01:22:48.120 | 2010-12-29T01:22:48.120 | null | null | 1679 | null |
5801 | 1 | 5805 | null | 1 | 314 | Sorry if this is a n00b question, I'm just trying to wrap my head around the problem. I am trying to refute conventional wisdom here, so any help is greatly appreciated.
And now for the question:
For example, I flip a coin 100 times and I end up with 50 consecutive heads followed by 50 consecutive tails. How would I ca... | Is it possible to predict the likelihood of an order of random events? | CC BY-SA 2.5 | null | 2010-12-29T06:09:32.537 | 2010-12-29T09:30:18.017 | 2010-12-29T06:13:55.593 | 183 | 2131 | [
"probability",
"randomness"
] |
5802 | 2 | null | 4356 | 17 | null | Rpart only provides univariate splits. I believe, based upon your question, that you are not entirely familiar with the difference between a univariate partitioning method and a multivariate partitioning method. I have done my best to explain this below, as well as provide some references for further research and to su... | null | CC BY-SA 2.5 | null | 2010-12-29T06:58:48.683 | 2010-12-30T06:06:56.613 | 2010-12-30T06:06:56.613 | 2166 | 2166 | null |
5805 | 2 | null | 5801 | 2 | null | You have some event with certain probability of success. So the probability that the next time this event happens is the success probability. In your case you have flipped coin 100 times with 50 consecutive heads and 50 consecutive tails. The probability of this event happening is $1/2^{100}$. If you repeat this experi... | null | CC BY-SA 2.5 | null | 2010-12-29T09:29:59.850 | 2010-12-29T09:29:59.850 | null | null | 2116 | null |
5806 | 2 | null | 5801 | 3 | null | The probability of 50 tails followed by 50 heads, assuming balanced iid bernoulli coins, is simply $\prod_{i=1}^{100} P(Event_i=Predicted_i)=\frac 1 2 ^{50} \times \frac 1 2 ^{50} = 2^{-100}$.
50/50 is just as unlikely as 49/51, if order must be preserved.
| null | CC BY-SA 2.5 | null | 2010-12-29T09:30:18.017 | 2010-12-29T09:30:18.017 | null | null | 2456 | null |
5807 | 1 | null | null | 6 | 1782 | Colleagues of mine recently presented a work where they calibrate boosted regression trees (BRT) models on small data sets ($n= 30$). They validated the models using leave-one-out cross validation (LOOCV) using R2, RMSPE and RPD indices. They also provided these indices computed by training and validating the model on ... | Leave-one-out cross validation and boosted regression trees | CC BY-SA 2.5 | null | 2010-12-29T14:31:10.063 | 2010-12-29T21:20:27.750 | 2010-12-29T17:28:11.153 | null | 2561 | [
"regression",
"machine-learning",
"cross-validation"
] |
5808 | 1 | 5809 | null | 7 | 9136 | One of the ANCOVA assumptions, as I read it [here](http://www.google.gr/url?sa=t&source=web&cd=2&sqi=2&ved=0CCoQFjAB&url=http%3A%2F%2F161.111.161.171%2Festadistica2004%2FANOVA%2FANCOVA.pdf&rct=j&q=ancova%20assumptions%20covariates%20independent%20randomization%20&ei=0UobTcOkKoey8gOq9rCeBQ&usg=AFQjCNFzfXuU154mlSPmMA8oN4... | Checking factor / covariate independence in ANCOVA | CC BY-SA 2.5 | null | 2010-12-29T15:14:45.243 | 2010-12-29T17:12:47.310 | null | null | 339 | [
"r",
"spss",
"ancova",
"assumptions"
] |
5809 | 2 | null | 5808 | 10 | null | One approach is to see if the covariate is correlated with the predictor variables. That is, if the ANCOVA is given by:
```
predicted ~ covariate + predictor1*predictor2*predictor3
```
Then first assess whether the covariate and the various predictor effects/interactions are correlated:
```
covariate ~ predictor1*pred... | null | CC BY-SA 2.5 | null | 2010-12-29T16:02:23.433 | 2010-12-29T16:35:50.477 | 2010-12-29T16:35:50.477 | 364 | 364 | null |
5810 | 2 | null | 5808 | 1 | null | EDIT As pointed out in the comments below, this is an answer to a different question, one about ensuring that the effect of the covariate is the same in all groups.
You have to check for interactions of the covariate and the factors. So if the ANCOVA model was
```
lm1 <- lm(outcome ~ covariate + factor1*factor2*factor... | null | CC BY-SA 2.5 | null | 2010-12-29T16:39:58.993 | 2010-12-29T17:12:47.310 | 2010-12-29T17:12:47.310 | 279 | 279 | null |
5812 | 2 | null | 5807 | 4 | null | It is hard to tell without data, but the set may be "too homogeneous" to make LOO work -- imagine you have a set $X$ and you duplicate all objects to make a set $X_d$ -- while BRT usually have very good accuracy on its train, it is pretty obvious that LOO on $X_d$ will probably give identical results to test-on-train.
... | null | CC BY-SA 2.5 | null | 2010-12-29T17:27:19.787 | 2010-12-29T21:20:27.750 | 2010-12-29T21:20:27.750 | null | null | null |
5813 | 1 | 5816 | null | 1 | 212 | I am a beginner level programmer preparing for the interview in medical research company. Job sounds damn interesting and I would like to get there.
To show my skills and interest, I want to write a program related to the topic.
I think, statistical analysis is quite used in that field, isn't it?
What would you suggest... | Demo for bioinformatics | CC BY-SA 2.5 | 0 | 2010-12-29T17:48:41.317 | 2010-12-29T22:09:28.347 | 2010-12-29T22:09:28.347 | 2564 | 2564 | [
"bioinformatics"
] |
5814 | 1 | null | null | 7 | 327 | [Traffic light synchronization](http://ops.fhwa.dot.gov/publications/fhwahop08024/chapter6.htm) nowadays is not a tedious project, Image:
For a personal research project I'm trying to build a statistical model to solve such problems in two and higher dimensions.
I would li... | Help in setting up and solving a transportation / traffic problem | CC BY-SA 2.5 | null | 2010-12-29T18:22:44.217 | 2011-06-25T12:45:38.133 | null | null | 59 | [
"monte-carlo",
"transportation"
] |
5816 | 2 | null | 5813 | 1 | null | Write a script that aligns short DNA fragments (25-100 basepairs) to an existing genome.
| null | CC BY-SA 2.5 | null | 2010-12-29T20:03:22.763 | 2010-12-29T20:03:22.763 | null | null | 1795 | null |
5817 | 1 | 5822 | null | 3 | 652 | I want to know if a covariate for each subject interacts with three types of trials, and the difficulty of those trials. My dependent measures are accuracy and response times (RT). For this question, I’d like to focus on RTs. Traditionally, people in my field have dichotomized the covariate of interest and used ANOVAs ... | What is my model statement for mixed models (nlme) in R? | CC BY-SA 3.0 | null | 2010-12-29T20:17:43.350 | 2013-09-04T14:36:18.880 | 2013-09-04T14:36:18.880 | 21599 | 2322 | [
"r",
"mixed-model",
"lme4-nlme"
] |
5818 | 2 | null | 5696 | 2 | null | Here's a couple of ways to think about.
1
A) You could treat each full sequence of codings as a ordered set of events (i.e. ["head nod", "head shake", "head nod", "eyebrow raised"] and ["head nod", "head shake", "eyebrow raised"]), then align the sequences using an algorithm that made sense to you ( [http://en.wikipedi... | null | CC BY-SA 2.5 | null | 2010-12-29T20:25:54.147 | 2010-12-30T21:38:28.320 | 2010-12-30T21:38:28.320 | 82 | 82 | null |
5819 | 1 | 5820 | null | 10 | 10924 | I am using [scipy.stats.gaussian_kde](http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.gaussian_kde.html) to estimate a pdf for some data. The problem is that the resulting pdf takes values larger than 1. As far as I understand, this should not happen. Am I mistaken? If so why?
| Kernel density estimate takes values larger than 1 | CC BY-SA 2.5 | null | 2010-12-29T20:27:46.593 | 2010-12-30T15:28:38.317 | 2010-12-30T15:28:38.317 | 919 | 977 | [
"distributions",
"probability",
"estimation",
"python"
] |
5820 | 2 | null | 5819 | 17 | null | You are mistaken. The CDF should not be greater than 1, but the PDF may be. Think, for example, of the PDF of a Gaussian random variable with mean zero and standard deviation $\sigma$:
$$f(x) = \frac{1}{\sqrt{2\sigma\pi}}\exp(-\frac{x^2}{2\sigma^2})$$
if you make $\sigma$ very small, then for $x = 0$, the PDF is arbitr... | null | CC BY-SA 2.5 | null | 2010-12-29T20:33:48.510 | 2010-12-29T20:33:48.510 | null | null | 795 | null |
5822 | 2 | null | 5817 | 1 | null | (This isn't an answer, simply an attempt at clarification of the question. I would have made this a comment to the question, but I haven't had success putting code in a comment)
Am I correct in interpreting your design as captured by the data frame resulting from the following (ignoring the arbitrary number of subjects... | null | CC BY-SA 2.5 | null | 2010-12-29T22:11:52.237 | 2010-12-29T22:11:52.237 | null | null | 364 | null |
5823 | 2 | null | 5791 | 6 | null | It seems to me that CV is inappropriate here. I think you may be better off separating the change in location from the change in dispersion. In addition, the distributions you mention in your comment to the question are, for most parameter values, skewed (positively, except for the beta distribution). That makes me que... | null | CC BY-SA 2.5 | null | 2010-12-29T22:49:05.940 | 2010-12-29T22:49:05.940 | null | null | 449 | null |
5824 | 2 | null | 5797 | 0 | null | Ok, duh, one approach would be to use the James-Stein shrinkage. This will not, I believe, unbias the estimates, but will reduce the mean squared error.
| null | CC BY-SA 2.5 | null | 2010-12-29T23:55:41.287 | 2010-12-29T23:55:41.287 | null | null | 795 | null |
5825 | 2 | null | 5791 | 6 | null | Some alternatives, which have the same 'flavor' as CV are:
- The coefficient of L-variation, see e.g. Viglione. The second sample L-moment takes the place of the sample standard deviation.
- The $\gamma$-Winsorized standard deviation divided by the $\gamma$-trimmed mean. You probably want to divide this by $1 - 2\gam... | null | CC BY-SA 2.5 | null | 2010-12-30T04:50:05.367 | 2010-12-30T04:50:05.367 | null | null | 795 | null |
5826 | 1 | 5830 | null | 10 | 14609 | I was wondering if anybody had experience in how to set the knot points when using cubic regression splines.
Some background: I have a response and predictor variable, and I want to determine the trend relationship between the two. To see what it looks like without making too many assumptions, I've fit a smoothing spli... | Knot selection for cubic regression splines | CC BY-SA 2.5 | null | 2010-12-30T05:53:33.917 | 2010-12-30T10:11:57.400 | null | null | 1569 | [
"regression",
"splines"
] |
5827 | 1 | null | null | 5 | 2474 | We work on cervical cancer detection and we started accumulating data in 2006 by performing HPV testing on all our samples. We have accumulated a data set with almost 400,000 women. Data enters the database on a daily basis. Most women come for a yearly smear so most women are more than one time in the database (2-13x)... | How do I calculate and compare incidence of infection between age-groups | CC BY-SA 2.5 | null | 2010-12-30T06:07:23.883 | 2011-08-15T13:15:32.400 | 2010-12-30T09:49:09.903 | 930 | 2571 | [
"epidemiology",
"stata",
"disease"
] |
5828 | 2 | null | 4356 | 1 | null | Multivariate splits as defined in the CART book aren't implemented in `rpart`. The CART software package from Salford Systems has this feature, but AFAIK it uses a proprietary algorithm licensed from Breiman, Friedman et al.
| null | CC BY-SA 2.5 | null | 2010-12-30T06:31:03.853 | 2010-12-30T06:31:03.853 | null | null | 1569 | null |
5829 | 2 | null | 5776 | 0 | null | This a job for Bayes Theorem, not for null-hypothesis testing. You've given us some information, so we should now simply determine how much more or less consistent that information is with the hypothesis than with its negation & adjust our priors accordingly. Based on what you've told us I conclude that the likelihood ... | null | CC BY-SA 2.5 | null | 2010-12-30T06:36:57.283 | 2010-12-30T06:36:57.283 | null | null | 11954 | null |
5830 | 2 | null | 5826 | 13 | null | This is a tricky problem and most people just select the knots by trial and error.
One approach which is growing in popularity is to use penalized regression splines instead. Then knot selection has little effect provided you have lots of knots. The coefficients are constrained to avoid any coefficient being too large... | null | CC BY-SA 2.5 | null | 2010-12-30T09:08:39.313 | 2010-12-30T09:08:39.313 | null | null | 159 | null |
5831 | 1 | 5883 | null | 18 | 748 | I think it is fair to say statistics is an applied science so when averages and standard deviations are calculated it is because someone is looking to make some decisions based on those numbers.
Part of being a good statistician then I would hope is being able to "sense" when the sample data can be trusted and when so... | War stories where wrong decisions were made based on statistical information? | CC BY-SA 3.0 | null | 2010-12-30T10:11:11.710 | 2016-12-20T19:25:02.097 | 2016-12-20T18:32:46.517 | 22468 | null | [
"references",
"inference",
"descriptive-statistics",
"history",
"fallacy"
] |
5832 | 2 | null | 5826 | 7 | null | It depends what you mean by "not too wiggly", but you might like to take a look at fractional polynomials for a simpler approach to fitting smooth curves that are not linear but not 'wiggly'. See [Royston & Altman 1994](http://www.jstor.org/stable/2986270) and the [mfp package](http://cran.r-project.org/web/packages/mf... | null | CC BY-SA 2.5 | null | 2010-12-30T10:11:57.400 | 2010-12-30T10:11:57.400 | null | null | 449 | null |
5833 | 2 | null | 3589 | 0 | null | Well a lot depends on the assumptions you make. If you assume that the data is stationary then more data for series one will give you abetter estimate of its volatility. This estimate can be used to improve the correlation estimate.
So the follwoing statment is incorrect:
"The history of Y's price before X went publi... | null | CC BY-SA 2.5 | null | 2010-12-30T10:58:21.897 | 2010-12-30T10:58:21.897 | null | null | null | null |
5834 | 1 | null | null | 2 | 904 | In a Markov chain, a state $j$ is transient if $f_{jj}<1$ ($f_{jj}$ is probability of ever visiting state $j$ starting from state $j$ ).
Suppose, I have an irreducible transient DTMC (means all states are transient). Now, I want to prove that for any $i,j$ in $S$ ($S$ is DTMC state space), $f_{ij}$ (i.e probability of ... | First passage time distribution in a irreducible transient discrete-time Markov chain (DTMC) | CC BY-SA 2.5 | null | 2010-12-30T10:58:50.857 | 2010-12-31T16:46:13.443 | 2010-12-30T17:17:09.033 | 449 | 2516 | [
"markov-process"
] |
5835 | 2 | null | 5827 | 0 | null | I don't use Stata or Prism 5, so I can't help with that part, but a survival analysis does sound appropriate, at least from what you've said. The most commonly used method is Cox proportional hazard, which is certainly available in Stata.
Instructions on how to code the data are program specific, so I will leave it ... | null | CC BY-SA 2.5 | null | 2010-12-30T12:58:23.283 | 2010-12-30T16:21:13.550 | 2010-12-30T16:21:13.550 | 449 | 686 | null |
5836 | 1 | 5838 | null | 7 | 1238 | This is more of a "how to use R" question than an actual hardcore statistics question, but I think the concentration of R masters here makes this a good forum for it. I'm refreshing a time series graphing package that currently uses gnuplot. The first step is getting somewhere close to the current graphs, and then I ho... | Annotating graphs in R | CC BY-SA 2.5 | null | 2010-12-30T15:06:34.093 | 2011-01-02T22:56:50.777 | 2010-12-30T16:27:12.743 | 930 | 2443 | [
"r",
"time-series",
"data-visualization",
"ggplot2"
] |
5837 | 2 | null | 5827 | 3 | null | Survival analysis is a good idea, but:
- Do not discard anybody - even those with only one data point. The fact that they did or did not have HPV at that age is informative.
- Your data is interval censored: left-censored for those who are positive at first measurement, right-censored for those who stay negative, and... | null | CC BY-SA 2.5 | null | 2010-12-30T15:34:32.293 | 2010-12-30T15:34:32.293 | null | null | 279 | null |
5838 | 2 | null | 5836 | 5 | null | A quick and dirty way to paste some text and numerical results along the labels of your legend is to simply rename the factor levels. For instance,
```
df <- data.frame(x=rnorm(100), y=rnorm(100), f=gl(2,50))
df$f2 <- df$f
levels(df$f2) <- paste(levels(df$f), tapply(df$y, df$f, mean), sep=": ")
p <- ggplot(data=df) + g... | null | CC BY-SA 2.5 | null | 2010-12-30T16:23:03.247 | 2010-12-30T16:23:03.247 | null | null | 930 | null |
5839 | 2 | null | 5836 | 6 | null | I'm sure that there's a more elegant way to do this but you can try this :
```
Data <- data.frame(serie1 = cumsum(rnorm(100)), serie2 = rnorm(100), temps = as.Date(1:100, origin = "2000-01-01"))
label <- c("In traffic [max 2.0G bps] [Avg 1.1G bps] [95% 1.8G bps] [Min 569.4M bps]", "Out traffic [max 2.0G bps] [Avg 672... | null | CC BY-SA 2.5 | null | 2010-12-30T16:59:30.710 | 2010-12-30T16:59:30.710 | null | null | 2028 | null |
5841 | 2 | null | 5327 | 4 | null | @Firefeather: Does your data contain (and can only really ever contain) only positive values? If so, model it using a generalized linear model with gamma error and log link. If it contains zeros then you could consider a two stage (logistic regression for probability of zero and gamma regression for the positive values... | null | CC BY-SA 2.5 | null | 2010-12-30T17:17:29.253 | 2010-12-30T17:17:29.253 | null | null | 2040 | null |
5842 | 1 | 5846 | null | 6 | 2700 | I have a load of point data in 3D, and I wish to cluster them like so:
- Each cluster contains points all of which are at most distance $d$ from another point in the cluster.
- All points in two distinct clusters are at least distance $d$ from each other.
The distances used are Euclidean distances.
Is this a well ... | Cluster data points by distance between clusters | CC BY-SA 2.5 | null | 2010-12-30T17:59:52.847 | 2010-12-30T20:04:33.040 | null | null | null | [
"clustering"
] |
5844 | 1 | null | null | 4 | 1879 | Working on probabilistic outputs of kernel methods I found the formulation of the SVM as a Penalized Method using the Binomial Deviance (described for example in "[The Elements of Statistical Learning Theory](http://www-stat.stanford.edu/~tibs/ElemStatLearn/), 2nd edition" by Hastie et al., pp 426--430). The model is c... | What is the connection between Kernel Logistic Regression and Smoothing Splines? | CC BY-SA 2.5 | null | 2010-12-30T19:53:26.203 | 2015-04-14T19:18:40.800 | 2015-04-14T19:18:40.800 | 9964 | 2549 | [
"machine-learning",
"logistic",
"svm",
"smoothing",
"kernel-trick"
] |
5845 | 1 | 5849 | null | 11 | 949 | Can the group recommend a good introduction text/resource to applied resampling techniques? Specifically, I am interested in alternatives to classical parametric tests (e.g. t tests, ANOVA, ANCOVA) for comparing groups when assumptions such as normality are clearly violated.
An example problem type I would like to edu... | Good text for resampling? | CC BY-SA 3.0 | null | 2010-12-30T19:53:29.647 | 2023-04-30T05:55:45.193 | 2017-02-25T18:00:27.267 | 11887 | 2040 | [
"references",
"bootstrap",
"resampling"
] |
5846 | 2 | null | 5842 | 4 | null | Create a graph in which the points are nodes and two points are connected with an edge if and only if they lie within distance $d$ of each other. Stated in these terms, your criteria become
- Every node in a cluster of two or more nodes is connected to at least one other node in that cluster.
- No two points in any ... | null | CC BY-SA 2.5 | null | 2010-12-30T20:04:33.040 | 2010-12-30T20:04:33.040 | null | null | 919 | null |
5847 | 1 | 5864 | null | 4 | 2454 | So, working in web analytics, it's common to use a chi-square test for A/B tests to test statistical significance. I often use a calculator like this: [http://www.usereffect.com/split-test-calculator](http://www.usereffect.com/split-test-calculator) , so if each variation gets 1000 impressions, and A has 100 conversion... | Statistical significance (chi squared) for percentages over 100%? | CC BY-SA 2.5 | null | 2010-12-30T20:08:04.423 | 2010-12-31T12:10:01.110 | 2010-12-30T20:42:34.797 | null | 142 | [
"chi-squared-test",
"hypothesis-testing"
] |
5848 | 2 | null | 5845 | 5 | null | Phillip Good, Permutation, Parametric, and Bootstrap Tests of Hypotheses (3rd Edition). Springer, 2005.
This book is mathematically easy, accessible, and covers a wide range of applications.
| null | CC BY-SA 2.5 | null | 2010-12-30T20:13:12.627 | 2010-12-30T20:13:12.627 | null | null | 919 | null |
5849 | 2 | null | 5845 | 7 | null | As for a good reference, I would recommend Philip Good, [Resampling Methods: A Practical Guide to Data Analysis](http://www.springer.com/birkhauser/applied+probability+and+statistics/book/978-0-8176-4386-7) (Birkhäuser Boston, 2005, 3rd ed.) for an applied companion textbook. And here is [An Annotated Bibliography for ... | null | CC BY-SA 4.0 | null | 2010-12-30T20:18:40.273 | 2023-04-30T05:55:45.193 | 2023-04-30T05:55:45.193 | 56940 | 930 | null |
5850 | 1 | 5851 | null | 4 | 601 | Given a random variable $X_1$ drawn from a distribution with cdf $F$, and random variables $X_2, \cdots,X_n$ drawn from another distribution with cdf $G$, what is the formula for the probability that $X_1$ is the $k$-th out of the $n$ variables, when they are sorted in order. If it helps, assume that $F$ and $G$ are b... | Order statistics: probability random variable is k-th out of n when ordered | CC BY-SA 2.5 | null | 2010-12-30T21:57:40.627 | 2010-12-31T10:33:41.713 | 2010-12-31T10:33:41.713 | 930 | 2582 | [
"order-statistics"
] |
5851 | 2 | null | 5850 | 6 | null | By computing the probability that $k-1$ of the $G$-distributed $X$'s are less than or equal to $X_1$, conditional on the value of $X_1 = t$, and integrating over all $t$ we obtain
$$\int_{-\infty}^{\infty}{\binom{n-1}{k-1} G(t)^{k-1}(1-G(t))^{n-k}dF(t)}.$$
This of course assumes independence of all the $X_i$. Given no... | null | CC BY-SA 2.5 | null | 2010-12-30T22:57:51.933 | 2010-12-30T22:57:51.933 | null | null | 919 | null |
5852 | 2 | null | 5844 | 3 | null | There is a book on "Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach" by [Green and Silverman](http://rads.stackoverflow.com/amzn/click/0412300400), that is probably a good start, but my copy is in my office, so I can't get it until the new year. Essentially IIRC, the link between k... | null | CC BY-SA 2.5 | null | 2010-12-31T00:02:24.833 | 2010-12-31T00:02:24.833 | null | null | 887 | null |
5853 | 1 | 5876 | null | 9 | 18341 | (This relates to my programming question on Stack Overflow: [Bell Curve Gaussian Algorithm (Python and/or C#)](https://stackoverflow.com/questions/4560554/).)
On Answers.com, I found this simple example:
- Find the arithmetic mean (average)
=> Sum of all values in the set, divided by the numbers of elements in the se... | Forcing a set of numbers to a gaussian bell-curve | CC BY-SA 3.0 | null | 2010-12-31T05:49:57.543 | 2016-10-15T20:52:19.757 | 2017-05-23T12:39:26.167 | -1 | 2585 | [
"algorithms",
"normal-distribution"
] |
5854 | 1 | null | null | 23 | 36273 | I am working on creating a website, which displays the census data for a user selected Polygons & would like to graphically show the distribution of various parameters (one graph per parameter).
The data usually has the following properties:
- The sample size tend to be large (say around 10,000 data points)
- The ran... | What are some alternatives to a boxplot? | CC BY-SA 2.5 | null | 2010-12-31T06:38:50.327 | 2022-11-24T16:23:39.150 | 2010-12-31T09:59:05.407 | 930 | 2586 | [
"distributions",
"data-visualization",
"boxplot"
] |
5856 | 2 | null | 5854 | 5 | null | Here is a [matlab function](http://www.mathworks.com/matlabcentral/fileexchange/23661-distribution-plot) for plotting multiple histograms side-by-side in 2D as an alternative to box-plot. See the picture on the top. And here is [another one](http://www.mathworks.com/matlabcentral/fileexchange/26508-notboxplot-alternati... | null | CC BY-SA 4.0 | null | 2010-12-31T09:18:51.613 | 2019-01-12T16:46:05.810 | 2019-01-12T16:46:05.810 | 339 | 339 | null |
5857 | 2 | null | 5854 | 4 | null | How about using quantiles? It is not necessary to present a graph then, only a table. For village census I think the users will be most interested how many there are villages of certain size, so giving for example deciles will tell them them information such as $x\%$ of all the villages are smaller than the certain num... | null | CC BY-SA 2.5 | null | 2010-12-31T09:37:33.170 | 2010-12-31T09:37:33.170 | null | null | 2116 | null |
5858 | 2 | null | 4949 | 33 | null | There's no closed form, but you could do it numerically.
As a concrete example, consider two Gaussians with following parameters
$$\mu_1=\left(\begin{matrix}
-1\\\\
-1
\end{matrix}\right),
\mu_2=\left(\begin{matrix}
1\\\\
1
\end{matrix}\right)$$
$$\Sigma_1=\left(\begin{matrix}
2&1/2\\\\
1/2&2
\end{matrix}\right),\ \Sig... | null | CC BY-SA 3.0 | null | 2010-12-31T09:41:57.923 | 2013-06-25T07:10:08.940 | 2013-06-25T07:10:08.940 | 2148 | 511 | null |
5859 | 1 | null | null | 21 | 11997 | I am confused about how to decide whether to treat time as continuous or discrete in survival analysis. Specifically, I want to use survival analysis to identify child- and household-level variables that have the largest discrepancy in their impact on boys' versus girls' survival (up to age 5). I have a dataset of chil... | Survival analysis: continuous vs discrete time | CC BY-SA 2.5 | null | 2010-12-31T10:10:49.467 | 2019-06-29T08:14:36.320 | 2019-06-29T08:14:36.320 | 3277 | 2587 | [
"survival",
"ties"
] |
5860 | 2 | null | 5854 | 5 | null | I rather like [violin plots](http://en.wikipedia.org/wiki/Violin_plot) myself, as this gives an idea of the shape of the distribution. However if the large range of values is the issue, then maybe it would be best to plot the log of the data rather than the raw values, that would then make choosing the box sizes for h... | null | CC BY-SA 2.5 | null | 2010-12-31T10:12:59.793 | 2010-12-31T11:57:20.967 | 2010-12-31T11:57:20.967 | 930 | 887 | null |
5861 | 2 | null | 5854 | 14 | null | A boxplot isn't that complicated. After all, you just need to compute the three [quartiles](http://en.wikipedia.org/wiki/Quartile), and the min and max which define the range; a subtlety arises when we want to draw the whiskers and various methods have been proposed. For instance, in a [Tukey boxplot](http://mathworld.... | null | CC BY-SA 4.0 | null | 2010-12-31T10:17:27.987 | 2022-11-24T16:23:39.150 | 2022-11-24T16:23:39.150 | 362671 | 930 | null |
5862 | 2 | null | 5854 | 8 | null | I'd suggest you persevere with histograms. They're much more widely understood than the alternatives. Use a log scale to cope with the large range of values. Here's an example I cooked up in a couple of minutes in Stata: 
I admit that the... | null | CC BY-SA 2.5 | null | 2010-12-31T11:13:59.307 | 2010-12-31T11:13:59.307 | 2020-06-11T14:32:37.003 | -1 | 449 | null |
5863 | 2 | null | 5854 | 2 | null | If you are targeting the general population (i.e. a non statistical-savvy audience) you should focus on eye-candy rather than statistical accuracy.
Forget about boxplots, let alone violin plots (I personally find them very difficult to read)! If you'd ask the average street man what a quantile is, you would mostly get ... | null | CC BY-SA 2.5 | null | 2010-12-31T11:14:35.397 | 2010-12-31T11:14:35.397 | null | null | 582 | null |
5864 | 2 | null | 5847 | 1 | null | I assume you have data on the amount of each donation, not just the two totals for each variation. You don't want to use [Pearson's chi-square test](http://en.wikipedia.org/wiki/Pearson%27s_chi-square_test); that's only appropriate for counts or proportions, not for amounts. You want an independent (unpaired) two-sampl... | null | CC BY-SA 2.5 | null | 2010-12-31T12:10:01.110 | 2010-12-31T12:10:01.110 | null | null | 449 | null |
5865 | 2 | null | 4551 | 4 | null | Using Analysis of Covariance (ANCOVA) to try to "control for" or "regress out" the influence of a covariate that is known to be correlated with, or affect the influence of, other predictor variables. More discussion at this question: [Checking factor/covariate independence in ANCOVA](https://stats.stackexchange.com/que... | null | CC BY-SA 2.5 | null | 2010-12-31T13:17:04.073 | 2010-12-31T13:17:04.073 | 2017-04-13T12:44:46.433 | -1 | 364 | null |
5866 | 2 | null | 5859 | 4 | null | I suspect if you use continuous time models you will want to use interval censoring, reflecting the fact that you don't know the exact time of failure, just an interval in which the failure ocurred. If you fit parametric regression models with interval censoring using maximum likelihhod the tied survival times is not ... | null | CC BY-SA 2.5 | null | 2010-12-31T14:30:55.177 | 2010-12-31T14:30:55.177 | null | null | 887 | null |
5867 | 2 | null | 2234 | 13 | null | There are around 100 classification and regression models which are trainable via the [caret package](https://cran.r-project.org/web/packages/caret/). Any of the classification models will be an option for you (as opposed to regression models, which require a continuous response). For example to train a random forest:
... | null | CC BY-SA 3.0 | null | 2010-12-31T14:56:21.053 | 2016-05-23T06:14:51.047 | 2016-05-23T06:14:51.047 | 75266 | 2589 | null |
5868 | 1 | 5869 | null | 3 | 177 | With real-valued $X_1, X_2, \ldots$, define
$Max_n := \max(X_1,\ldots,X_n)$ record value or high-water mark
$NextMax_n :=$ the next greater high water, $Max_{n+m} > Max_n$
$Up_n := NextMax_n - Max_n$.
Can anyone suggest an introduction to estimating $NextMax$ and $Up$, for
- $X$ i.i.d. from a known distribution,
- ... | Basics of extreme values / high-water marks? | CC BY-SA 2.5 | null | 2010-12-31T15:07:55.817 | 2011-01-01T15:44:40.887 | 2011-01-01T15:44:40.887 | 557 | 557 | [
"references",
"extreme-value"
] |
5869 | 2 | null | 5868 | 2 | null | Stuart Coles' [book](http://rads.stackoverflow.com/amzn/click/1852334592) on extreme value statistics would probably be a good place to start.
| null | CC BY-SA 2.5 | null | 2010-12-31T15:19:49.277 | 2010-12-31T15:19:49.277 | null | null | 887 | null |
5870 | 1 | 5875 | null | 4 | 293 | Lets say we have three independent variables:
$$\eqalign{
X_{1}\sim &B(n,\frac{1}{2}+\beta) \cr
X_{2}\sim &B(n,\frac{1}{2}) \cr
X_{3}\sim &B(n,\frac{1}{2}-\beta).
}$$
I'm looking for the distribution of
$$\max(X_{1},X_{2},X_{3})-\min(X_{1},X_{2},X_{3}).$$
For sufficiently large $n$ we have
$$\Pr(\max(X_{1},X_{2}... | The range of non-identically distributed binomial variables | CC BY-SA 2.5 | null | 2010-12-31T15:25:01.957 | 2010-12-31T21:45:34.447 | 2010-12-31T21:45:34.447 | 919 | 1643 | [
"distributions",
"random-variable",
"approximation"
] |
5871 | 2 | null | 5834 | 3 | null | Your claim is false: there exist transient Markov chains such that $f_{ij}=1$ for some (but not all) states $i$ and $j$.
For example, assume that the state space is the union of the discrete halfline $\mathbb{Z}_+$ and of a discrete circle $\mathbb{Z}/N\mathbb{Z}$ with $N\ge3$, the halfline and the circle meeting at $... | null | CC BY-SA 2.5 | null | 2010-12-31T15:42:51.813 | 2010-12-31T16:46:13.443 | 2010-12-31T16:46:13.443 | 2592 | 2592 | null |
5872 | 2 | null | 5870 | 3 | null | Call $R_n=\max(X_1,X_2,X_3)-\min(X_1,X_2,X_3)$. The usual LLN shows that $R_n/n$ converges to $2\beta$ almost surely and in $L^1$. (The distribution of $R_n$ for a given fixed $n$ is an altogether different story.)
| null | CC BY-SA 2.5 | null | 2010-12-31T15:58:09.770 | 2010-12-31T15:58:09.770 | null | null | 2592 | null |
5873 | 1 | null | null | 6 | 1147 | I would like to test a hypothesis that a database contains data that are correct in 95% or more of the samples.
I found this [Hypothesis test for a proportion](http://stattrek.com/Lesson5/Proportion.aspx?Tutorial=AP) experiment design that looked appropriate.
I will randomly sample one-tenth of the population and mark ... | Experiment design for proportion | CC BY-SA 2.5 | null | 2010-12-31T16:02:54.980 | 2011-01-07T20:05:42.093 | null | null | 2591 | [
"experiment-design",
"proportion"
] |
5874 | 1 | 5878 | null | 3 | 689 | The greatest gain of the statistics classes in both school and university seems to be that I now have an inkling of which QA site to use for this question. :)
I'm a programmer and I'm making a questionnaire with a financial background. There will be many (probably over 100) questions, which will be presented to the use... | How to best estimate the time remaining for a variable-length questionnaire? | CC BY-SA 2.5 | null | 2010-12-31T16:15:37.393 | 2017-06-12T16:58:22.613 | 2017-06-12T16:58:22.613 | 11887 | 2590 | [
"estimation",
"winsorizing"
] |
5875 | 2 | null | 5870 | 4 | null | For $n \le 20$ just compute the distribution by brute force.
For example, with $n=3$ the pdf is
$$\begin{array}{}
k=0: &-\frac{7}{64} \left(-1+4 \beta ^2\right)^3 \cr
k=1: &\frac{39}{256} \left(1-4 \beta ^2\right)^2 \left(3+4 \beta ^2\right) \cr
k=2: &-\frac{3}{128} \left(-15-92 \beta ^2+560 \beta ^4+192 \beta ^6\r... | null | CC BY-SA 2.5 | null | 2010-12-31T17:11:08.333 | 2010-12-31T17:11:08.333 | null | null | 919 | null |
5876 | 2 | null | 5853 | 13 | null | A scaled range, like 200 to 800 (for SATs, e.g.), is just a change of units of measurement. (It works exactly like changing temperatures in Fahrenheit to those in Celsius.)
The middle value of 500 is intended to correspond to the average of the data. The range is intended to correspond to about 99.7% of the data when... | null | CC BY-SA 2.5 | null | 2010-12-31T17:47:11.673 | 2011-01-09T16:55:51.487 | 2011-01-09T16:55:51.487 | 919 | 919 | null |
5877 | 2 | null | 5853 | 4 | null | You could try this approach - normalise your data set to range between the values -1 and +1 thus:
$$
\left(\frac{\text{individual_value} - \text{min_of_all_values}}{\text{max_of_all_values} - \text{min_of-all_values}}-0.5\right)*2.
$$
This will convert every value in your data set to a value between -1 and +1, with t... | null | CC BY-SA 3.0 | null | 2010-12-31T18:58:15.357 | 2012-12-13T15:17:01.830 | 2012-12-13T15:17:01.830 | 7290 | 226 | null |
5878 | 2 | null | 5874 | 3 | null | I do not see why averages should not work. You might want to use [winsorized](http://en.wikipedia.org/wiki/Winsorized_mean) or [trimmed](http://en.wikipedia.org/wiki/Trimmed_mean) averages to guard against outliers, which are likely due to inability to tell exactly whether user is idle or not. Then for the estimated... | null | CC BY-SA 2.5 | null | 2010-12-31T19:06:34.287 | 2010-12-31T20:34:31.280 | 2010-12-31T20:34:31.280 | 2116 | 2116 | null |
5879 | 2 | null | 5874 | 3 | null | As @mpiktas points out, simple is good. But I can't help thinking there will be substantial variation among users. Roughly, we can conceive of the time to complete each question as depending on the question and on the user, so the trick is to tease out the question-specific timing factors from the experience of previ... | null | CC BY-SA 2.5 | null | 2010-12-31T21:35:13.707 | 2010-12-31T21:35:13.707 | null | null | 919 | null |
5880 | 1 | 5881 | null | 7 | 2068 |
The probability of that a number between 1 to x is prime is $\frac{1}{\ln{x}}$ as per prime number theorem and also the total number of prime numbers between $1$ to $x$ will be $\frac{x}{\ln{x}}$.
But if we select $n$ (32 bit) random numbers, what is the probability that $p$ of them are primes?
Or Simply put
What is t... | What is the probability of picking p primes from n random numbers? | CC BY-SA 2.5 | null | 2011-01-01T09:48:45.877 | 2011-01-27T23:45:44.303 | 2011-01-01T18:07:23.237 | null | 2597 | [
"probability"
] |
5881 | 2 | null | 5880 | 16 | null | There are 203,280,221 primes less than $2^{32}$. ([Source](http://www.ieeta.pt/~tos/primes.html)). So the probability that a random 32-bit number is prime is $203,280,221 / 2^{32} \approx 0.04733$. Assuming you want selection with replacement, i.e. the same number can be picked more than once, the probability of pickin... | null | CC BY-SA 2.5 | null | 2011-01-01T10:20:34.620 | 2011-01-27T23:45:44.303 | 2011-01-27T23:45:44.303 | 919 | 449 | null |
5882 | 2 | null | 1980 | 4 | null | Robert Gentleman wrote a paper called ["Reproducible Research: A Bioinformatics Case Study"](http://www.bepress.com/sagmb/vol4/iss1/art2/)
It implements a short set of analyses as an R Package and uses Sweave.
It also discusses the use of Sweave more generally.
See the ["Related Files"](http://www.bepress.com/sagmb/vol... | null | CC BY-SA 2.5 | null | 2011-01-01T10:35:17.683 | 2011-01-01T10:35:17.683 | null | null | 183 | null |
5883 | 2 | null | 5831 | 7 | null | This isn't exactly what you're asking for, but I think you'd like David Freedman's work. He calls BS on misapplication of statistical tests, etc... See here: [http://www.stat.berkeley.edu/~freedman/](http://www.stat.berkeley.edu/~freedman/). One of my favorites is “What is the probability of an earthquake?”.
| null | CC BY-SA 2.5 | null | 2011-01-01T22:49:18.977 | 2011-01-01T22:49:18.977 | null | null | 2489 | null |
5885 | 1 | null | null | 36 | 15971 | Any suggestions for a good source to learn MCMC methods?
| Good sources for learning Markov chain Monte Carlo (MCMC) | CC BY-SA 3.0 | null | 2011-01-02T03:16:43.820 | 2021-05-18T15:56:24.433 | 2015-01-16T12:17:58.473 | 22228 | 2601 | [
"references",
"markov-chain-montecarlo"
] |
5886 | 2 | null | 5885 | 6 | null | [Gilks W.R., Richardson S., Spiegelhalter D.J. Markov Chain Monte Carlo in Practice. Chapman & Hall/CRC, 1996.](http://books.google.co.uk/books?id=TRXrMWY_i2IC)
A relative oldie now, but still a goodie.
| null | CC BY-SA 2.5 | null | 2011-01-02T07:36:06.087 | 2011-01-02T07:36:06.087 | null | null | 449 | null |
5887 | 1 | 5888 | null | 9 | 453 | We have a set biological samples that was pretty expensive to obtain. We put these samples through a series of tests to generate data that are used for building a predictive model. For this purpose we have divided the samples to training (70%) and testing (30%) sets. We have successfully created a model and applied it ... | Should I re-shuffle my data? | CC BY-SA 2.5 | null | 2011-01-02T08:31:58.303 | 2012-01-22T20:51:15.340 | 2012-01-22T20:51:15.340 | 930 | 2604 | [
"classification",
"modeling",
"experiment-design",
"cross-validation",
"bootstrap"
] |
5888 | 2 | null | 5887 | 12 | null | As you already use a holdout sample, I would say you should keep it and build your new models on the same training sample so that all models will consider the same relationships between features. In addition, if you perform feature selection, the samples must be left out before any of these filtering stages; that is, f... | null | CC BY-SA 2.5 | null | 2011-01-02T09:22:46.873 | 2011-01-02T20:40:16.190 | 2011-01-02T20:40:16.190 | 919 | 930 | null |
5889 | 2 | null | 5885 | 16 | null | For online tutorials, there are
- A tutorial in MCMC, by Sahut (2000)
- Tutorial on Markov Chain Monte Carlo, by Hanson (2000)
- Markov Chain Monte Carlo for Computer Vision, by Zhu et al. (2005)
- Introduction to Markov Chain Monte Carlo simulations and their statistical analysis, by Berg (2004).
- A Tutorial on ... | null | CC BY-SA 4.0 | null | 2011-01-02T09:32:02.837 | 2021-05-18T15:56:24.433 | 2021-05-18T15:56:24.433 | 296197 | 930 | null |
5890 | 2 | null | 5885 | 9 | null | I haven't read it (yet), but if you're into R, there is Christian P. Robert's and George Casella's book:
[Introducing Monte Carlo Methods with R (Use R)](http://rads.stackoverflow.com/amzn/click/1441915753)
I know of it from following his (very good) [blog](http://xianblog.wordpress.com/)
| null | CC BY-SA 3.0 | null | 2011-01-02T10:17:49.443 | 2015-01-16T07:23:13.243 | 2015-01-16T07:23:13.243 | 7224 | 253 | null |
5891 | 2 | null | 5885 | 4 | null | [Dani Gamerman & Hedibert F. Lopes. Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference (2nd ed.). Boca Raton, FL: Champan & Hall/CRC, 2006. 344 pp. ISBN 0-412-81820-5](http://books.google.co.uk/books?id=yPvECi_L3bwC).
-- a more recently updated book than Gilks, Richardson & Spiegelhalter. I haven't ... | null | CC BY-SA 2.5 | null | 2011-01-02T11:20:10.533 | 2011-01-02T12:06:00.227 | 2011-01-02T12:06:00.227 | 930 | 449 | null |
5893 | 1 | null | null | 12 | 1812 | A name: first, possibly a middle, and surname.
I'm curious about how much information you can mine out of a name, using publicly available datasets. I know that you can get the following with anywhere between a low-high probability (depending on the input) using US census data:
1) Gender.
2) Race.
Facebook for instance... | How much information can you mine out of a name? | CC BY-SA 2.5 | null | 2011-01-02T17:04:44.293 | 2023-05-01T07:05:12.343 | null | null | null | [
"dataset",
"data-mining",
"census"
] |
5894 | 1 | 5897 | null | 4 | 133 | I am new to statistics so I apologize for the simplicity of my question.
I have a bag with 27 numbers inside; I will pull one number out until I get number 17. THe numbers will be returned to the bag after every try so the prob of success will always be 1/27.
I am trying to determine on average how many pulls I will n... | Number of tried for a favorable result | CC BY-SA 2.5 | null | 2011-01-02T17:52:18.390 | 2011-01-03T00:10:55.017 | null | null | 2610 | [
"binomial-distribution",
"negative-binomial-distribution"
] |
5895 | 2 | null | 5894 | 2 | null | It is easier to think backwards. What is the chance of NOT choosing 17? That chance is 26/27. What is the chance of not choosing 17 twice in a row? The answer is (26/27)(26/27). How about three times in a row? The answer is (26/27)(26/27) *(26/27). More generally, the answer is (26/27)^K, where K is the number of time... | null | CC BY-SA 2.5 | null | 2011-01-02T17:59:57.440 | 2011-01-02T17:59:57.440 | null | null | 25 | null |
5896 | 2 | null | 5894 | 3 | null | On average, you need 27 tries.
| null | CC BY-SA 2.5 | null | 2011-01-02T19:07:29.217 | 2011-01-02T19:07:29.217 | null | null | 2592 | null |
5897 | 2 | null | 5894 | 2 | null | Harvey explained the logic. But the name of the distribution you're interested in is the geometric distribution.
| null | CC BY-SA 2.5 | null | 2011-01-02T19:14:42.883 | 2011-01-02T19:14:42.883 | null | null | 1028 | null |
5898 | 2 | null | 5893 | 4 | null | From the first name predict region, age, first generation immigrant status. From the last name you could predict geographical location of original patronym. For the full name you could predict social and economic status (Thurston Howell III).
| null | CC BY-SA 2.5 | null | 2011-01-02T20:43:26.670 | 2011-01-02T20:43:26.670 | null | null | 82 | null |
5899 | 1 | 5905 | null | 5 | 398 | Imagine a committee of people in charge of hiring a CEO. A committee member can vote "No hire" (+0), "Maybe"(+1), "Hire"(+2) for a potential CEO candidate. Each CEO is scored based on the votes, and the CEO with the highest score is hired.
Now, imagine a situation where two candidates are tied... both of them have a ... | What to do about ties in voting results? | CC BY-SA 3.0 | null | 2011-01-02T21:14:13.577 | 2019-06-29T08:21:26.367 | 2019-06-29T08:21:26.367 | 3277 | 2605 | [
"ties",
"voting-system"
] |
5900 | 2 | null | 5885 | 6 | null | [Handbook of Markov Chain Monte Carlo, Steve Brooks, Andrew Gelman, Galin Jones and Xiao-Li Meng, eds. 2011 CRC Press.](http://www.crcpress.com/product/isbn/9781420079418;jsessionid=AYSwK8euwh4-aVy7BXE2wQ%2a%2a)
[Chapter 4](http://www.stat.columbia.edu/~gelman/research/published/GelmanMCMCchapter4.pdf), 'Inference fro... | null | CC BY-SA 2.5 | null | 2011-01-02T21:39:14.060 | 2011-01-02T21:39:14.060 | null | null | 1381 | null |
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