Learning Objectives

1.2. Learning Objectives#

Here is what you should understand after this week

1.2.1. Conceptual#

After this week you should:

  • Understand what a null and alternative hypothesis are

  • Understand the procedure for null hypothesis testing (ie assume the null is true, work out the probability of our test statistic arising)

  • Understand that the null distribution is the distribution of the test statistic under the null hypothesis

  • Understand that the null distribution can be estimated empirically by permutation of the sample

  • Understand which datapoints may be permuted to test for:

    • A difference of means in independent samples

    • A mean (pairwise) difference in paired samples

    • A correlation

The conceptual material is covered in the lecture and recapped in the worked examples in Python

1.2.2. Python skills#

The key skill practiced this week is running a permutation test using scipy.stats

To do that, you will need to be able to create very simple functions

This material is covered in the Jupyter Notebooks in this section

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