Inferential Statistics: hypothesis testing

Inferential statistics draws conclusions about a population on the basis of data from a sample. In general we set out to

1. Generate a research hypothesis
2. Cast this as a statistical hypothesis
3. Decide which test statistic can test the hypothesis and compute the statistic
4. Determine the significance of the statistic by examining its p value
5. Evaluate the statistical hypothesis

A statistical hypothesis is tested by first constructing the null hypothesis. Typically the null hypothesis is of the form there is no difference between these variables or groups or there is no association between these variables, one does not affect the value of the other. The alternative hypothesis is that there is an association or difference. We hope that if we design our study carefully and formulate the hypotheses carefully then rejection of the null hypothesis will compel us to accept the alternative.

Notes

Contents

1 Introduction

2 Statistical Measure

3 Parametric and Non-parametric Methods

4 Descriptive Statistics

5 Inferential Statistics: hypothesis testing

6 Degrees of freedom

7 Significance

8 Association

9 Comparing groups or variables

10 Regression