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Teaching the IA analysis section can feel daunting, especially with the statistical components. 

But don’t worry—breaking it down and guiding students through the process step-by-step makes it manageable. 

Remember: your students should be doing most of the work, and with the right approach, you can keep calm and confident!

Understanding Levels of Data

One of the first things to get clear on is understanding different levels of data—nominal, ordinal, interval/ratio—because the type of data collected influences which statistical tests are appropriate. 

Even though students no longer need to justify their choice of tests in the mark scheme, their tests must still be suitable. 

Encourage them to add a sentence explaining their test choice to signpost that their selection is appropriate. 

For instance, mode is appropriate for nominal data, while median and range (or interquartile range) work well with ordinal data. 

For interval/ratio data, students should use the mean and standard deviation. 

Also, consider percentages and ratios if the study calls for them.

Presenting Data Clearly

Although tables aren’t required in the mark scheme, they’re a great way to present descriptive statistics in an organised manner. 

Ensure that students label all their tables and graphs correctly, including operationalised variables. 

Speaking of graphs, the mark scheme does require their correct presentation, so take time to go over the rules for proper graph formatting. 

Labelling is key here—clear, properly labeled graphs make a great impression on examiners.

Using Online Calculators and Justifying Test Choices

Online statistics calculators are a lifesaver for students, allowing them to handle calculations without getting bogged down in math. 

Encourage students to include screenshots of their calculations in the appendix and refer to them in the main body (e.g., “see Appendix X”). 

For inferential statistics, students again need to choose the right test. 

While they don’t need to justify their choice in the official write-up, having them do it helps solidify their understanding. 

Make sure they grasp the concept of significance, as this is crucial for interpreting their findings.

Interpreting Results in Relation to the Hypothesis

The final step in the analysis is where students must interpret both their descriptive and inferential statistics in relation to their research and null hypotheses. 

This is a critical part of the IA. 

Students should clearly state whether their results support the research hypothesis or the null hypothesis, and explain why. 

By linking their statistical results to their hypothesis, they demonstrate their understanding of the research process.

I hope this has helped clarify the process, so you can teach the IA analysis section with confidence and calm.

Best of luck, and have a fantastic week ahead!

Thes

Future articles in this series:

• Demystifying referencing systems.
• Marking, grading and providing feedback on IB Psychology IAs.
• Avoiding IA trip wires.