Introduction
Class 1: May 24
- Topic: Overview of the course, Introduction to R
- Textbook: Chapter 1 (Section 1.3)
- Pre-class Exercise:
qsslearnr Tutorial 0: Introduction
to R
Causality
Class 2: May 26
- Topic: Randomized experiments
- Textbook: Chapter 2 (Sections 2.1–2.4)
- Pre-class Exercise:
qsslearnr Tutorial 1: Causality
I
Class 3: May 31
- Topic: Observational studies
- Textbook: Chapter 2 (Sections 2.5–2.7)
- Pre-class Exercise:
qsslearnr Tutorial 2: Causality
II
Measurement
Class 4: June 2
- Topic: Survey sampling
- Textbook: Chapter 3 (Sections 3.1–3.4)
- Pre-class Exercise:
qsslearnr Tutorial 3: Measurement
I
Class 5: June 7
- Topic: Clustering
- Textbook: Chapter 3 (Sections 3.5–3.7)
- Pre-class Exercise:
qsslearnr Tutorial 4: Measurement
II
Prediction
Class 6: June 9
- Topic: Prediction and Loop
- Textbook: Chapter 4 (Section 4.1)
- Pre-class Exercise:
qsslearnr Tutorial 5: Prediction
I
Class 7: June 14
- Topic: Regression
- Textbook: Chapter 4 (Sections 4.2–4.3)
- Pre-class Exercise:
qsslearnr Tutorial 6: Prediction
II
Midterm Exam
Final Exam Period: June 15 -
22
Class 8: June 16
No class due to the midterm exam
Probability
Class 9: June 21
- Topic: Probability and conditional probability
- Textbook: Chapter 6 (Sections 6.1–6.2)
- Pre-class Exercise:
qsslearnr Tutorial 7: Probability
I
Class 10: June 23
- Topic: Random variables and their distributions, Large sample
theorems
- Textbook: Chapter 6 (Sections 6.3–6.4)
- Pre-class Exercise:
qsslearnr Tutorial 8: Probability
II
Uncertainty
Class 11: June 28
- Topic: Estimation
- Textbook: Chapter 7 (Section 7.1)
- Pre-class Exercise:
qsslearnr Tutorial 9: Uncertainty
I
Class 12: June 30
- Topic: Hypothesis tests
- Textbook: Chapter 7 (Section 7.2)
- Pre-class Exercise:
qsslearnr Tutorial 10: Uncertainty
II
Class 13: July 5
- Topic: Regression with uncertainty
- Textbook: Chapter 7 (Section 7.3)
- No pre-class exercise
Final Exam
Final Exam Period: July 11 -
18