Lectures schedule (L02)

Tutorials schedule
(T05/T06/T07)

Tuesday/Thursday
15:3016:45
(ST 135)

Wednesday
13:0013:50 (BIO182) Wednesday 13:0013:50 (MS521) Wednesday 15:0015:50 (MS571) 
Class
work:
Inclass lectures with typical examples (lecture notes will be posted
on the webpage in the form of pdffiles);
your computer must have an Adobe Acrobat reader (for free downloading
see www.adobe.com).
Midterm
and Quizzes:
There will be 1 Midterm ( Nov 9, 2006) and 5 Quizzes.
Final
Exam:
It will cover all the materials covered in this course.
Grading scheme (Course Evaluation):
Exam, Midterm and Quizzes

Value (% of your final mark)

Dates

Midterm

25%

November 9, Thu, 15:3016:45 (ST135) 
Quizzes (5)

25%=5x5%
(5% for each quiz)

Oct 11, Oct 25, Nov 8, Nov 22, Dec 6

Final Exam  50%  13 December, Wednesday, 3:30pm5:30pm, ICT 121. 
Month 
Day 
Tuesday 
Day 
Thursday 
Sep 
12 
Lec1:
Introduction to Probability: Probability and Inference. A Review of Set
Notation (Sections 2.12.3). 
14  Lec2:
The Discrete Case Probability Model. Probability of Events. Counting
Sample Points (Sections 2.42.6). 
Sep 
19 
Lec3:Conditional
Probability and Independence. Two Laws of Probability. Event
Composition Method (Sections 2.72.9). 
21 
Lec4:
Law of Total Probability and Bayes' Rule. Numerical Events and Random
Variables. Random Sampling (Sampling 2.102.12) 
Sep 
26 
Lec5:
Definitions of Discrete Random Variables. Distributions, Expected Value
and Variance of Discrete
Random Variables (Sections 3.13.3) 
28 
Lec
6: Properties of the Expected Value and Variance of a
Random Variable. (Section 3.3) 
Oct 
3 
Lec7: Binomial Distribution (Sections 3.4)  5 
Lec8: Geometric Distribution, Negative
Binomial Distribution. Hypergeometric
Distribution. (Sections 3.5.3.7) 
Oct 
10 
Lec9:
Poisson
Distribution (Section 3.8) 
12 
Lec10:
MomentGenerating Function, Tchebysheff's Theorem (Sections 3.9,
3.11) 
Oct 
17 
Lec11:
Distribution of Continuous Random Variables (CRV) (Sections
4.14.2) 
19 
Lec12:
Expected Value for CRV.Uniform Distribution (Sections 4.34.4) 
Oct 
24 
Lec13: Normal Distribution (Section 4.5).  26 
Lec14: Gamma Distribution (Section 4.6) 
OctNov 
31 
Lec15:
The Beta Distribution and Other Expected Values (Section 4.84.9) 
2 
Lec16:
Tchebysheff's Theorem (Section 4.10) 
Nov 
7 
Lec17:
Definition of Sampling: Normal Distribution (Section 7.17.2) 
9 
Midterm. 
Nov 
14 
Reading Day (No Lecture) 
16 
Lec18: The Central Limit
Theorem. The Normal
Approximation to Binomial Distribution. (Sections 7.3,7.5) 
Nov 
21 
Lec19: Estimation: Confidence
Intervals. (Sections 8.1,8.2,8.5) 
23 
Lec20: LargeSample
Confidence Intervals and Selecting
the Sample Size (Sections 8.6, 8.7) 
Nov 
28 
Lec21: Hypothesis
Testing: Definition. Statistical Tests (Sections 10.110.2) 
30 
Lec22: LargeSample
Test. (Section 10.3) 
Dec 
5 
Lec23: Type II Error
Probabilities and Sample Size for the Z Test (Sections
10.4, 10.6) 
7 
Lec24: SmallSample
Hypothesis Testing (Section 10.8). 
Your Marks for Final Exam are Available 
Marks
for FINAL EXAM, MIDTERM and Quizzes Answers to MIDTERM and Quizzes (15) 