Statistics and Research Methods - Part 2: Data Analysis and Hypothesis Testing

Learn to test hypotheses and interpret statistical results

Find new ways to test whether your research findings are meaningful or just due to chance. Once you know how to explore data, the next step is testing ideas with confidence.

This course introduces core tools of hypothesis testing, showing you how to compare groups, estimate uncertainty, and interpret statistical results in context. It’s designed for learners who want practical understanding rather than just formulae.

You’ll develop skills to move from description to formal analysis with confidence.

Understand hypothesis testing

Learn how statistical hypotheses are formed and how tests are used to evaluate them. You’ll explore confidence intervals, p-values, and statistical significance in a clear and applied way.

Understanding these concepts helps you connect statistical tests to real research questions meaningfully.

Compare groups with confidence

Practise using common parametric tests, including one-sample, two-sample, and paired approaches. You’ll learn how to decide which method is appropriate for a given question and dataset.

These skills help you move from description to formal analysis with greater confidence and rigour.

Interpret results responsibly

Focus on what results mean in context, not just whether they’re statistically significant. You’ll learn how assumptions affect tests and why interpretation matters as much as calculation.

By the end of this course, you’ll be better equipped to draw careful conclusions from data and communicate findings appropriately.

This course is ideal for students, researchers, and professionals who need to compare groups and interpret statistical findings in applied settings without requiring advanced mathematical background.

This course is ideal for students, researchers, and professionals who need to compare groups and interpret statistical findings in applied settings without requiring advanced mathematical background.

• Discuss the fundamental principles of statistical hypothesis testing and uncertainty.
• Identify appropriate parametric tests for comparing means across different group structures.
• Classify the components of a confidence interval and its associated p-value.
• Describe the concept of statistical significance within a given research context.