ABSTRACT

Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work. Although there are many approaches to teaching statistics, a common framework exists between them: starting with probability and distributions, then sampling from distribution and descriptive statistics and later introducing both simple and complex statistical tests, typically ending with regression analysis (linear models).

This book proposes to reverse the way statistics is taught, by starting with the introduction of linear models. Today, many statisticians know that the one unifying principle of statistical tests is that most of them are instances of linear models. This teaching method has two advantages: all statistical tests in a course can be presented under the same unifying framework, simplifying things; second, linear models can be expressed as lines over squared paper, replacing any equation with a drawing.

This book explains how and why statistics works without using a single equation, just lines and squares over grid paper. The reader will have the opportunity to work through the examples and compute sums of squares by just drawing and counting, and finally evaluating whether observed differences are statistically significant by using the tables provided. Intended for students, scientists and those with little prior knowledge of statistics, this book is for all with simple and clear examples, computations and drawings helping the reader to not only do statistical tests but also understand statistics.

chapter 1|10 pages

What Is Statistics?

chapter 2|5 pages

Know Your Samples

chapter 3|12 pages

Estimating Populations

chapter 4|10 pages

The Design of Experiments

chapter 5|9 pages

Comparing Two Variances

chapter 6|7 pages

One Sample

chapter 7|9 pages

Two Samples

chapter 8|4 pages

Why Squares? (At Last!)

chapter 9|9 pages

More Than Two Samples

chapter 10|13 pages

Two-Way

chapter 11|11 pages

Regression

chapter 12|9 pages

What If My Data Is Not 'Normal'?

chapter 13|6 pages

Counting

chapter 14|5 pages

Size, Power and Effects