Elementary Statistics with R

In hypothesis testing, a type II error is due to a failure of rejecting an invalid null hypothesis. The probability of avoiding a type II error is called the power of the hypothesis test, and is denoted by the quantity 1 - β .

A tutorial on computing the kurtosis of an observation variable in statistics.

A tutorial on computing the skewness of an observation variable in statistics.

A tutorial on computing the central moments of an observation variable in statistics.

We use the logistic regression equation to predict the probability of a dependent variable taking the dichotomy values 0 or 1. Suppose x₁, x₂, ..., x_p are the independent variables, α and β_k (k = 1, 2, ..., p) are the parameters, and E(y) is the expected value of the dependent variable y, then the logistic regression equation is:

A tutorial of performing statistical analysis with the Kruskal-Wallis test.

A tutorial of performing statistical analysis with the Mann-Whitney-Wilcoxon test.

A tutorial of performing statistical analysis with the Wilcoxon signed-rank test.

A tutorial of performing statistical analysis with the sign test.

A statistical method is called non-parametric if it makes no assumption on the population distribution or sample size.

This is in contrast with most parametric methods in elementary statistics that assume the data is quantitative, the population has a normal distribution and the sample size is sufficiently large.