Chapter 3. Using R to introduce basic concepts of hypothesis testing

This chapter explains the logic used to test hypotheses from a frequentist perspective (i.e., the perspective most commonly taught for data analysis).

Along the way we also introduce these concepts:

Population vs. sample
Sampling error
Randomization test
Null vs. alternative hypotheses, and why the null hypothesis is so important
Null distribution
p-values: what are they and how do we interpret them?

Introduction to analysing data

We introduce these concepts by analysing data collected by citizen scientists, which can be found at this link here:

Link to data from the Edinburgh DataShare website

We will analyse these real data to determine whether the average 'leaf' data (ie date at which a tree opens it's first leaf) for Beech trees differs between Northern vs Southern UK. You will learn to answer this question using a 'randomization test', which is a very useful tool.

Download work book, slides and data sets here:

Experimental data chapter 3 Computer Practical Slides (3.62 MB / PDF)

Experimental data chapter 3 Computer Practical Workbook (276.34 KB / PDF)

Experimental data chapter 3 Beech data (7.62 KB / CSV)

Experimental data chapter 3 Diff data (1.14 KB / CSV)