Data analysis: hypothesis testing

Introduction

In this course, you will explore the process of testing hypotheses and making inferences about data. This will typically be a collection of individuals in a population in the statistical sense (people, companies, countries, etc.), and the quantity of interest will be a parameter describing the population.

You will learn about descriptive statistics, alpha (α) and confidence intervals as well as the distinction between one-tailed and two-tailed tests, and the concept of ‘p-value’. Furthermore, you will gain insight into how to test for differences in means and proportions. Ultimately, you will gain knowledge about the concept of ‘tests for statistical significance’.

Figure 1 Data sheds light on hypotheses

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The picture portrays a professor conducting an open lecture on the moon, with a tag line displayed at the bottom which states, ‘Surprisingly, the soil samples provide new evidence for the “giant ball of cheese” hypothesis.’

Figure 1 Data sheds light on hypotheses

This course requires Microsoft Excel in some activities therefore this course should be completed on a desktop or laptop rather than a mobile device. If you do not have access to Microsoft Excel there are various other free options – such as Google Sheets, Apple Numbers or LibreOffice.

This OpenLearn course is an adapted extract from the Open University course B126 Business data analytics and decision making [Tip: hold Ctrl and click a link to open it in a new tab. (Hide tip)] .