Statistical Analysis Stack Exchange
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Difference between naive Bayes & multinomial naive Bayes

I've dealt with Naive Bayes classifier before. I've been reading about Multinomial Naive Bayes lately. Also Posterior Probability = (Prior * Likelihood)/(Evidence). The only prime difference (while programming these classifiers) I found between…
garak
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Why does Andrew Ng prefer to use SVD and not EIG of covariance matrix to do PCA?

I am studying PCA from Andrew Ng's Coursera course and other materials. In the Stanford NLP course cs224n's first assignment, and in the lecture video from Andrew Ng, they do singular value decomposition instead of eigenvector decomposition of…
DongukJu
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Computing Cohen's Kappa variance (and standard errors)

The Kappa ($\kappa$) statistic was introduced in 1960 by Cohen [1] to measure agreement between two raters. Its variance, however, had been a source of contradictions for quite a some time. My question is about which is the best variance…
Cesar
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What is the difference between a population and a sample?

What is the difference between a population and a sample? What common variables and statistics are used for each one, and how do those relate to each other?
Baltimark
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3 answers

What kind of information is Fisher information?

Suppose we have a random variable $X \sim f(x|\theta)$. If $\theta_0$ were the true parameter, the the likelihood function should be maximized and the derivative equal to zero. This is the basic principle behind the maximum likelihood estimator. As…
Stan Shunpike
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What does the term saturating nonlinearities mean?

I was reading the paper ImageNet Classification with Deep Convolutional Neural Networks and in section 3 were they explain the architecture of their Convolutional Neural Network they explain how they preferred using: non-saturating nonlinearity…
Charlie Parker
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What exactly is Big Data?

I have been asked on several occasions the question: What is Big-Data? Both by students and my relatives that are picking up the buzz around statistics and ML. I found this CV-post. And I feel that I agree with the only answer there. The…
Gumeo
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How to interpret and report eta squared / partial eta squared in statistically significant and non-significant analyses?

I have data that has eta squared values and partial eta squared values calculated as a measure of effect size for group mean differences. What is the difference between eta squared and partial eta squared? Can they both be interpreted using the…
Short Elizabeth
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How to calculate a confidence level for a Poisson distribution?

Would like to know how confident I can be in my $\lambda$. Anyone know of a way to set upper and lower confidence levels for a Poisson distribution? Observations ($n$) = 88 Sample mean ($\lambda$) = 47.18182 what would the 95% confidence look…
Travis
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Compendium of cross-validation techniques

I'm wondering if anybody knows of a compendium of cross-validation techniques with a discussion of the differences between them and a guide on when to use each of them. Wikipedia has a list of the most common techniques, but I'm curious if there are…
Amelio Vazquez-Reina
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Why does inversion of a covariance matrix yield partial correlations between random variables?

I heard that partial correlations between random variables can be found by inverting the covariance matrix and taking appropriate cells from such resulting precision matrix (this fact is mentioned in http://en.wikipedia.org/wiki/Partial_correlation,…
michal
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How to interpret F- and p-value in ANOVA?

I am new to statistics and I currently deal with ANOVA. I carry out an ANOVA test in R using aov(dependendVar ~ IndependendVar) I get – among others – an F-value and a p-value. My null hypothesis ($H_0$) is that all group means are equal. There…
JanD
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How to determine the optimal threshold for a classifier and generate ROC curve?

Let say we have a SVM classifier, how do we generate ROC curve? (Like theoretically) (because we are generate TPR and FPR with each of the threshold). And how do we determine the optimal threshold for this SVM classifier?
RockTheStar
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How can I test if given samples are taken from a Poisson distribution?

I know of normality tests, but how do I test for "Poisson-ness"? I have sample of ~1000 non-negative integers, which I suspect are taken from a Poisson distribution, and I would like to test that.
David B
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6 answers

What is your favorite statistical graph?

This is a favorite of mine This example is in a humorous vein (credit goes to a former professor of mine, Steven Gortmaker), but I am also interested in graphs that you feel beautifully capture and communicate a statistical insight or method, along…
Alexis
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