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There is a whole body of statistical method to deal with Multiplicity. This entails using various types of ANOVAs (depending on your hypothesis testing framework) and numerous related Post Hoc tests …

I have been told many times that the Anderson Darling (AD) test is much better than the Kolmogorov-Smirnov (KS) one because AD does a better job at fitting the tails of the distribution. KS is only g …

You raise an interesting question. First thing first, if you have an observation of 0.35, a mean of 0.25, and a standard deviation of 1/10^7 (that's how I interpret your e^-7 bit) you really don't ne …

You so often come across in the press various studies that conclude directionally opposite results. Those can be related to the testing of a new prescription drug or the merit of a specific nutrient …

Yes, I think all three mentioned tests will give you valid information regarding the difference in average stock returns. The t-test is already pretty good because it relies on the t distribution t …

Parametric most often means that a test assumes the tested variables are Normally distributed. Such tests often use regular nominal values, and look at differences in Averages. Non-parametric tests …

First, no model is perfect unless it is over-fit. So, your false positive rate is not unusual. Is a false positive rate of 16% good or bad? If it is lower than the natural proportion in the data it …

The Chi Square test (Goodness-of-Fit test) will be very good at comparing the tails of two distributions since it is structured to compare two distributions by buckets of values (graphically represent …

You nicely answered your own question. None of the four samples come anywhere near being Normally distributed, especially in the tails which is where distribution deviation most often occurs. It is …

I came across a situation where a large retailer is testing a new retail program. It selected specific pilot retail stores to test this program. Next, it selected a control group of retail stores so …

The first table tells you that the pre- and post-average test scores are radically different. The hypothesis you test is that they are indeed different. Such scores are so different as not needing s …

I would argue the opposite... and that as far as tests for Normal distributions are concerned, Jarque-Bera is the most transparent and explicit since it captures a combination of Skewness and Kurtosis …

Looking at a between-groups ANOVA situation, what do you get by actually doing such an ANOVA test first, and second do post-hoc (Bonferroni, Šidák, etc.) or planned comparisons tests? Why not skip the …

I understand Tukey's HSD is the most common post-hoc test for between-groups ANOVA. It appears some do not recommend or select it as a post-hoc test for within-groups ANOVA. Instead, they prefer Bonf …

I can't give you additional reasons to use the Kolmogorov-Smirnov test. But, I can give you an important reason not to use it. It does not fit the tail of the distribution well. In this regard, a s …