Chapter 3: Statistical Topics in Experimental Design

Sometimes the only thing you can do with a poorly designed experiment is to try to find out what it died of.

R. A. Fisher

Introduction

Sample Size and Power

Power

Power Analyses

Power Examples

Replication and Pseudoreplication

Randomization and Preventing Bias

Variation and Variables

Some Definitions

Relationships Between Variables

Just to Make Life Interesting

Introduction

Computer programmers have an acronym for writing code that applies equally well to the analysis of data by statistics: GIGO! Which, of course, signifies “Garbage In, Garbage Out.” As data analysts, we must remember that the data we are called upon to analyze usually has to be collected based on some type of experiment, ...

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