The curriculum is defined to be all that is covered in lectures, exercises, and topics from the course book. This includes also the Exercises and Miscellanea sections. The main focus in the lectures and exercises is on Chapter 6-9, but Chapters 1-5 and partly Chapter 10 are prerequisite for this.

• Chapter 1: Probability theory.
• Chapter 2: Transformations and expectations.
• Chapter 3: Common families of distributions.
• Chapter 4: Multiple random variables.
• Chapter 5: Properties of a random sample.
• Chapter 6: Principles of data reduction.
• Chapter 7: Point estimation. NOT 7.2.4 The EM Algorithm,
• Chapter 8: Hypothesis testing.
• Chapter 9: Interval estimation.
• Chapter 10: Asymptotic evaluations.