Learning Objectives

1.2. Learning Objectives#

1.2.1. Conceptual#

After this week you should understand the following concepts:

  • Definition of probability for discrete and continuous variables

  • Statistical independence

  • Conditional probability \((pA|B)\)

  • Joint probability \(p(A \cap B)\)

  • Marginal probability

  • Bayes Theorem

You should be able to understand the following probability diagrams

  • Probability tree

  • Contingency Table

  • Bar plot

This material is covered in both the video (on the introductory page for this chapter) and the text in the chapter

1.2.2. Python skills#

There are no new Python skills, however there are some exercises asking you to find joint and conditional probabilities in an actual dataset, by identifying the relevant rows in a pandas dataframe.

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