# Posts Tagged ‘ Probability and Statistics ’

## Robustness and tests for equal variance

May 16, 2018
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The two-sample t-test is a way to test whether two data sets come from distributions with the same mean. I wrote a few days ago about how the test performs under ideal circumstances, as well as less than ideal circumstances. This is an analogous post for testing whether two data sets come from distributions with the same […]

## Two-sample t-test and robustness

May 11, 2018
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A two-sample t-test is intended to determine whether there’s evidence that two samples have come from distributions with different means. The test assumes that both samples come from normal distributions. Robust to non-normality, not to asymmetry It is fairly well known that the t-test is robust to departures from a normal distribution, as long as the actual […]

## Sensitivity of logistic regression prediction on coefficients

May 4, 2018
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The output of a logistic regression model is a function that predicts the probability of an event as a function of the input parameter. This post will only look at a simple logistic regression model with one predictor, but similar analysis applies to multiple regression with several predictors. Here’s a plot of such a curve […]

## Obesity index: Measuring the fatness of probability distribution tails

April 23, 2018
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A probability distribution is called “fat tailed” if its probability density goes to zero slowly. Slowly relative to what? That is often implicit and left up to context, but generally speaking the exponential distribution is the dividing line. Probability densities that decay faster than the exponential distribution are called “thin” or “light,” and densities that […]

## Categorical Data Analysis

April 14, 2018
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Categorical data analysis could mean a couple different things. One is analyzing data that falls into unordered categories (e.g. red, green, and blue) rather than numerical values (e..g. height in centimeters). Another is using category theory to assist with the analysis of data. Here “category” means something more sophisticated than a list of items you […]

## Hypothesis testing vs estimation

April 3, 2018
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I was looking at my daughter’s statistics homework recently, and there were a pair of questions about testing the level of lead in drinking water. One question concerned testing whether the water was safe, and the other concerned testing whether the water was unsafe. There’s something bizarre, even embarrassing, about this. You want to do […]

## Generalized normal distribution and kurtosis

March 30, 2018
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The generalized normal distribution adds an extra parameter β to the normal (Gaussian) distribution. The probability density function for the generalized normal distribution is Here the location parameter μ is the mean, but the scaling factor σ is not the standard deviation unless β = 2. For small values of the shape parameter β, the […]

## Making sense of a probability problem in the WSJ

January 1, 2018
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Someone wrote to me the other day asking if I could explain a probability example from the Wall Street Journal. (“Proving Investment Success Takes Time,” Spencer Jakab, November 25, 2017.) Victor Haghani … and two colleagues told several hundred acquaintances who worked in finance that they would flip two coins, one that was normal and […]

## How can a statistician help a lawyer?

December 9, 2017
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I’ll be presenting at a webinar on Wednesday, December 13 at 1:00 PM Eastern. The title of the presentation is “Seven questions a statistician and answer for an attorney.” I will discuss, among other things, when common sense applies and when correct analysis can be counter-intuitive. There will be ample time at the end of […]

## Pareto distribution and Benford’s law

November 16, 2017
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The Pareto probability distribution has density for x ≥ 1 where a > 0 is a shape parameter. The Pareto distribution and the Pareto principle (i.e. “80-20” rule) are named after the same person, the Italian economist Vilfredo Pareto. Samples from a Pareto distribution obey Benford’s law in the limit as the parameter a goes to […]

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