Day | Lecture/Exercise session |
Preliminary Contents |
---|---|---|
Mon. 3 Sep. 11:00 - 12:00 |
Lecture Room HA4 |
Introduction to the course |
Mon. 3 Sep. 13:15 - 15:00 |
Lecture Room HB3 |
Basic definitions and probability laws (MA) Chapters 1, 2 |
Tue. 4 Sep. 10:00 - 11:45 |
Exercise session Rooms ES61, ES62, ES63 |
VLE |
Wed. 5 Sep. 10:00 - 11:45 |
Lecture Room HC1 |
Discrete random variables (MA) Chapters 3.1 - 3.5 |
Thu. 6 Sep. 10:00 - 11:45 |
Exercise session Rooms ES61, ES62, ES63 |
VLE |
Mon. 10 Sep. 13:15 - 15:00 |
Lecture Room HB3 |
Continuous random variables (MA) Chapters 4.1, 4.2, 4.4 - 4.6 |
Tue. 11 Sep. 10:00 - 11:45 |
Exercise session Rooms ES61, ES62, ES63 |
VLE |
Wed. 12 Sep. 10:00 - 11:45 |
Lecture Room HC1 |
Joint probability distributions (MA) Chapters 5.1 - 5.3 |
Thu. 13 Sep. 10:00 - 11:45 |
Exercise session Rooms HC105, ES62, ES63 |
VLE |
Mon. 17 Sep. 13:15 - 15:00 |
Lecture Room HB3 |
Introduction to Markov chains (GS) Chapter 11.1 |
Tue. 18 Sep. 10:00 - 11:45 |
Exercise session Rooms ED2480, ES62, ES63 |
VLE |
Wed. 19 Sep. 10:00 - 11:45 |
Lecture Room HC1 |
Introduction to Poisson processes (MA) Chapters 3.8, 4.3 |
Thu. 20 Sep. 10:00 - 11:45 |
Exercise session Rooms HC105, MT12, MT13, MT14 |
VLE Test 1 1. Axioms of probability and general additional rule 2. Discrete probability densities and distribution functions 3. Counting combinations 4. Simple probability on cross-tabulated data 5. Continuous probability densities and distriubtion functions 6. Normal distribution 7. Expectation, variance and their properties |
Mon. 24 Sep. 13:15 - 15:00 |
Lecture Room HB3 |
Estimation and confidence intervals, central limit theorem (MA) Chapters 6.1, 6.3, 7.1, Theorem 7.3.4, 7.4, 8.1, 8.2 |
Tue. 25 Sep. 10:00 - 11:45 |
Exercise session Rooms ES51, ES52 |
(MA) Exercises 7.47, 7.48, 7.49, 7.53, 7.55, 7.56, 8.23, 8.24 |
Wed. 26 Sep. 10:00 - 11:45 |
Lecture Room HC1 |
Confidence intervals (continued), introduction to statistical tests (MA) Chapters 6.1, 6.3, 7.1, Theorem 7.3.4, 7.4, 8.1, 8.2 |
Thu. 27 Sep. 10:00 - 11:45 |
Exercise session Rooms HC105, ES62, ES63 |
VLE |
Thu. 27 Sep. 13:15 - 14:00 |
Exercise session Rooms HC105, ES62 |
VLE |
Mon. 1 Oct. 13:15 - 15:00 |
Lecture Room HB3 |
Inferences on proportions (MA) Chapters 9.1, 9.3 |
Tue. 2 Oct. 10:00 - 11:45 |
Exercise session Rooms ES61, ES62, ES63 |
VLE |
Wed. 3 Oct. 10:00 - 11:45 |
Lecture Room HC1 |
Comparing two means (MA) Chapters 10.1, 10.3, 10.4 |
Thu. 4 Oct. 10:00 - 11:45 |
Exercise session Rooms HC105, ES62, ES63 |
VLE |
Fri. 5 Oct. 09:00 - 09:45 |
Exercise session Rooms ES61 |
VLE |
Mon. 8 Oct. 13:15 - 15:00 |
Lecture Room HB3 |
Generating functions |
Tue. 9 Oct. 10:00 - 11:45 |
Exercise session Rooms ES51, ES52 |
(EG) Exercise 6.18bc (A) Exercises 13.2.1, 13.2.3, 13.3.11, 13.3.23, 13.3.37 |
Wed. 5 Sep. 10:00 - 11:45 |
Lecture Room HC1 |
Moment generating functions, law of large numbers (MA) Chapters 3.4 (m.g.f. sec.), 7.3 (GS) Chapter 8 |
Thu. 11 Oct. 10:00 - 11:45 |
Exercise session Rooms ES51, ES52 |
(MA) Exercises 3.32, 3.34 (GS) Exercises 8.1.4, 8.1.8, 8.2.1, 8.2.2, 8.2.10 |
Mon. 15 Oct. 13:15 - 15:00 |
Lecture Room HB3 |
Linear regression (MA) Chapters 11.1, 11.2, 11.3 |
Mon. 15 Oct. 15:15 - 17:00 |
Exercise session Rooms ES51, ES52, ES53 |
Question and answer session, project consultation |
Tue. 16 Oct. 10:00 - 11:45 |
Exercise session Rooms ES61, ES62, ES63 |
VLE |
Wed. 17 Sep. 10:00 - 11:45 |
Lecture Room HC1 |
Introduction to non-parameteric tests, revision (MA) Chapter 10.6 |
Thu. 18 Oct. 10:00 - 11:45 |
Exercise session Rooms HC105, MT12, MT13, MT14 |
VLE Test 2 1. Central limit theorem 2. Confidence interval on the mean of a normal population with known variance, 3. The normal approximation to the binomial distribution 4. Confidence interval on a proportion 5. Central limit theorem for a sample mean |
Sat. 20 Oct. |
Written Exam |
|
Week | Theme | Exercises |
---|---|---|
1 |
Interpreting probabilities (MA 1.1) Sample spaces and events (MA 1.2) Permutations and combinatorics (MA 1.3) Axioms of probability (MA 2.1) Conditional probability (MA 2.2) Independence of the multiplication rule (MA 2.3) Bayes' theorem (MA 2.4) Dicrete probability densities (MA 3.2) Expectation and distribution parameters (MA 3.3) Geometric distribution (MA 3.4) Binomial distribution (MA 3.5) |
1.4 1.5, 1.6, 1.7 1.11, 1.12, 1.13, 1.14, 1.21, 1.24, 1.27 2.3, 2.4, 2.5, 2.6, 2.11 2.13, 2.14, 2.16, 2.39 2.19, 2.26, 2.40 2.36, 2.41 3.7, 3.9, 3.10, 3.13 3.14, 3.16, 3.17, 3.20, 3.21 3.24(abc), 3.31 3.41, 3.42 |
2 |
Continuous densities (MA 4.1) Expectation and distribution parameters (MA 4.2) Normal distribution (MA 4.4) Normal probability rule and Chebyshev's inequality (MA 4.5) Normal approximation to the binomial distribution (MA 4.6) Joint densities and independence (MA 5.1) Expectation and covariance (MA 5.2) Correlation (MA 5.3) |
4.1, 4.3, 4.5, 4.6, 4.9, 4.12, 4.71 4.15, 4.17, 4.18, 4.19, 4.22, 4.70 4.41, 4.43 4.47, 4.48, 4.49 4.52, 4.57 5.1, 5.3, 5.5, 5.9, 5.12 5.16, 5.21, 5.24, 5.25, 5.26 5.29, 5.30, 5.33 |
3 |
Markov chains (GS 11.1) Absorbing markov chains (GS 11.2) Poisson distribution (MA 3.8) Exponential distribution (MA 4.3) |
11.1.1, 11.1.8, 11.1.9, 11.1.10, 11.1.19 11.2.1, 11.2.2, 11.2.3 3.47, 3.48 4.34, 4.35, 4.36, 4.37 |
4 |
Random sampling (MA 6.1) Sample statistics (MA 6.3) Distribution of sample mean (MA 7.3) Interval estimation and central limit theorem (MA 7.4) Interval estimation of variability (MA 8.1) Estimating the mean and the Student's t-distribution (MA 8.2) Hypothesis testing (MA 8.3) |
6.1, 6.4 6.17, 6.24 (b, c, d, e) 7.44, 7.45, 7.46 7.49, 7.50 8.1, 8.2, 8.3, 8.5 8.10, 8.12, 8.13, 8.17 8.21, 8.24 |
5 |
Estimating proportions (MA 9.1) Comparing two proportions (MA 9.3) Point estimation: independent samples (MA 10.1) Comparing means: variance equal (MA 10.3) Comparing means: variance unequal (MA 10.4) |
9.1, 9.2, 9.4, 9.8 9.19, 9.20, 9.21, 9.23 10.1, 10.3, 10.4 10.12, 10.14, 10.16, 10.17, 10.18, 10.19 10.21, 10.23, 10.24, 10.26, 10.28 |
6 |
(A 13.2) (A 13.3) Moment generating function (MA 3.4) Distribution of sample mean (MA 7.3) |
13.2.7, 13.2.9 13.3.13, 13.3.35, 13.3.21 3.31, 3.35 7.38, 7.45 |
7 |
Model and parameter estimation (MA 11.1) Properties of least-squares estimators (MA 11.2) Confidence interval estimation (MA 11.3) Alternative nonparametric methods (MA 10.6) |
11.1, 11.7, 11.10 11.11, 11.12 11.16, 11.20, 11.23 10.37, 10.38, 10.39 |
Note that the tests and examination will consist of
similar questions in a similar interface, so learn with Stats VLE
and Have fun!
Assignment |
Date of issue |
Deadline |
---|---|---|
Wed. 12 Sep. |
Mon. 24 Sep. |
|
Mon. 24 Sep. |
Mon. 8 Oct. |
|
Wed. 3 Oct |
Mon. 15 Oct |
Points | Percentage |
Grade |
---|---|---|
[12 - 18) |
40% - 60% |
3 |
[18 - 24) |
60% - 80% |
4 |
[24 - 30] |
80% - 100% |
5 |