Lecture notes
Overview of Probability Theory
(Chapters 1-5)
Lectures 1, 2a: Survey sampling (Chapter 7)
Lectures 2b, 3: Estimation
of parameters (Chapters 8 and 6)
Lecture 4, 5a: Testing
hypotheses (Chapter 9)
Lectures 5b, 6a: Summarizing
data (Chapter 10)
Lectures 6b, 7: Introduction
to Bayesian inference (pages: 20-23, 94-96, 285-296, 329-331, 443-444)
Lectures 8, 9a: Comparing two
samples (Chapter 11)
Lectures 9b, 10, 11a: Analysis
of variance (Chapter 12)
Lectures 11b, 12: Categorical
data analysis (Chapter 13)
Lectures 13, 14: Multiple
regression (Chapter 14)
Grading system
1. A
set of optional INDIVIDUAL assignments can give a student up to 3 bonus points
depending on how many assignments are worked out and how well the reports are
written.
2. The final exam is
closed books. However, you will be allowed to use four A4 pages of notes. These
notes should be your own summary of the course material and might be either
hand-written or printed out from your own file. You are allowed to use a
calculator of type Casio FX82, Texas TI30 or Sharp EL531.
Max. number of units for the final exam is 30. Passing units (including
eventual bonus points for the optional assignment)
CTH
students: 12 for '3', 18 for '4', 24 for '5'
GU
students: 12 for 'G', 20 for 'VG'
Here comes a check list of topics that should be studied before the
final exam.
3.
When grading exams, I use the next signs
underline
- a place where it starts getting wrong or a wrong answer
three
dots - the answer is not complete
question
sign - I do not understand here or disagree
plus
- you made a good point here