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Table of Contents

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Basics

Introduction

Data analysis steps

Kinds of biological variables

Probability

Hypothesis testing

Confounding variables

 

Tests for nominal variables

Exact test of goodness-of-fit

Power analysis

Chi-square test of goodness-of-fit

G–test of goodness-of-fit

Chi-square test of independence

G–test of independence

Fisher's exact test

Small numbers in chi-square and G–tests

Repeated G–tests of goodness-of-fit

Cochran–Mantel– Haenszel test

 

Descriptive statistics

Central tendency

Dispersion

Standard error

Confidence limits

 

Tests for one measurement variable

One-sample t–test

Two-sample t–test

Independence

Normality

Homoscedasticity

Data transformations

One-way anova

Kruskal–Wallis test

Nested anova

Two-way anova

Paired t–test

Wilcoxon signed-rank test

 

Tests for multiple measurement variables

Linear regression and correlation

Spearman rank correlation

Polynomial regression

Analysis of covariance

Multiple regression

Simple logistic regression

Multiple logistic regression

 

Multiple tests

Multiple comparisons

Meta-analysis

 

Miscellany

Using spreadsheets for statistics

Displaying results in graphs

Displaying results in tables

Introduction to SAS

Choosing the right test

Choosing the right test

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This page was last revised December 4, 2014. Its address is http://www.biostathandbook.com/outline.html . It may be cited as:
McDonald, J.H. 2014. Handbook of Biological Statistics (3rd ed.). Sparky House Publishing, Baltimore, Maryland.

©2014 by John H. McDonald. You can probably do what you want with this content; see the permissions page for details.