h. Which pairs of means are statistically different?

To determine which pairs of means are statistically different, you would typically perform a statistical test, such as a t-test or ANOVA (Analysis of Variance), depending on the number of groups you are comparing.

Here are the steps:

1. Collect your data: You need to have data from at least two groups to compare their means.

2. Choose the appropriate test: If you are comparing the means of two groups, a t-test is appropriate. If you are comparing the means of three or more groups, ANOVA is the better choice.

3. Check assumptions: Both t-tests and ANOVA assume that your data is normally distributed and that variances are equal across groups. You can check these assumptions using tests like the Shapiro-Wilk test for normality and Levene's test for equality of variances.

4. Perform the test: You can perform these tests using statistical software. The software will give you a p-value.

5. Interpret the results: If the p-value is less than your chosen significance level (often 0.05), then you can conclude that there is a statistically significant difference between the means of the groups.

6. Post-hoc tests: If you are using ANOVA and find a significant result, you will need to perform post-hoc tests to find out which specific pairs of means are different.

Remember, a statistically significant result does not necessarily mean that the difference is large or important, just that it is unlikely to have occurred by chance.