MATH 321 (Fall 2007)
"Mathematical Probability"
Course Outline
Instructor:
Anatoliy Swishchuk
E-mail: aswish@ucalgary.ca
Office: MS552
Tel.: (403) 220-3274
Office Hours: TR: 11:00am-11:50am

Teaching Assistant (T06/T07):
Wong, Pik Tan (MS 326)
piktan@math.ucalgary.ca
Tel: 220-7983

Place: EDC 386

Lectures Schedule and Tutorials 
Lectures schedule (L02)
Tutorials  schedule (T05/T06/T07)
Tuesday/Thursday  15:30-16:45  (EDC 386)
 T05/07: Wednesday 13:00-13:50 (MS521)
 T06: Wednesday 15:00-15:50 (MS571)

Syllabus:
Sample spaces, Discrete probability, Discrete and continuous random variables, Standard distributions,
Mathematical expectations and variance, Moments and moment generating functions, Central limit theorem,
 Introduction to statistical inference

Course Information Sheet
Additional Course Information
An Introduction to R


 Important Class Dates:
First day of class: 15:30, Tuesday, September 11, 2007;
Quiz # 1: September 26, Wed, 13:00-13:50 (T05 /T07 MS521), 15:00-15:50 (T06 MS571)
Quiz # 2: October 10, Wed, 13:00-13:50 (T05/T07 MS521), 15:00-15:50 (T06 MS571)
Midterm: October 23, Tuesday, 15:30-16:45 (in-class)
Quiz # 3: November 21, Wed, 13:00-13:50  (T05/T07 MS521), 15:00-15:50 (T06 MS571)
Quiz # 4:  December 5, Wed, 13:00-15:50  (T05 /T07 MS521), 15:00-15:50 (T06 MS571)
Last day of class: December 6 (Thu), 2007.
 
Final Exam:
Thu, December 13, 3:30-5:30pm, KN AUX

Recommended text:
'Mathematical Statistics with Applications' by D.D. Wackerly, W.M. Mendenhall and R.L. Scheaffer, 6th ed., 2002, Duxbury Press.

Course Web Page:
The current official syllabus for this course is available in the wall pockets across from MS 476 and
on the webpage at www.math.ucalgary.ca Course Listing-Undergraduate.
There is also a web page for this course which contains the course outline, tentative course schedule,  grading scheme, important class dates, etc.
Announcements made in class will be posted there (see end of this web-page). The address of this web page is: http://www.math.ucalgary.ca/~aswish/math321F07.html/

Class work:
In-class lectures with typical examples (lecture notes will be posted on the webpage in the form of pdf-files
);
your computer must have an Adobe Acrobat reader (for free downloading see www.adobe.com).

Midterm and Quizzes:
There will be 1 Midterm ( Oct 23, 2007) and 4 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
15%
October 23, Tuesday, 15:30-16:45 (EDC 386)
Quizzes (4)
35%
Sept 26, Oct 10, Nov 21, Dec 5
Final Exam 50% Thu, December 13, 3:30-5:30pm, KN AUX


Tentative Lectures Schedule for MATH 321 Fall 2007
Month
Day
Tuesday
Day
Thursday
Sep
11
Lec1: Introduction to Statistics: Probability and Inference. A Review of Set Notation. Introduction to Probability. (Sections 1.1, 1.4, 2.1-2.3).
13 Lec2: Foundations of Probability. The Discrete Case Probability Model. Probability of Events. Counting Sample Points (Sections 2.4-2.6).
Sep
18
Lec3:Conditional Probability and Independence. Two Laws of Probability. Event Composition Method (Sections 2.7-2.9). Answers to some even-numbered exercises.
20
Lec4: Law of Total Probability and Bayes' Rule. Numerical Events and Random Variables. Random Sampling (Sections 2.10-2.12)
Sep
25
Lec5: Definitions of Discrete Random Variables. Distributions, Expected Value and Variance of Discrete Random Variables (Sections 3.1-3.2)
27
Lec 6:  Properties of the Expected Value and Variance  of a Random Variable.  (Section 3.3)
Oct
2
Lec7: Binomial Distribution (Sections  3.4)  4
Lec8: Geometric Distribution, Negative Binomial Distribution. Hypergeometric Distribution. (Sections 3.5.-3.7)
Oct
9
Lec9: Poisson Distribution (Section 3.8)
11
Lec10: Moment-Generating Function, Tchebysheff's Theorem (Sections 3.9,  3.11)
Oct
16
Lec11: Distribution of Continuous Random Variables (CRV)  (Sections 4.1-4.2)
18
Lec12:  Expected Value for CRV.Uniform Distribution (Sections 4.3-4.4)
Oct
23
Midterm 25
Lec13:  Normal Distribution (Section 4.5).
Oct-Nov
30
Lec14: Gamma Distribution (Section 4.6) 1
Lec15: The Beta Distribution and Other Expected Values (Section 4.8-4.9)
Nov
6
Lec16: Tchebysheff's Theorem (Section 4.10)
8
Lec17: Definition of Sampling: Sampling Related to Normal Distribution (Section 7.1-7.2)
Nov
13
Reading Day (No Lecture)
15
Lec18: The Central Limit Theorem. The Normal Approximation to Binomial Distribution. (Sections 7.3, 7.5)
Nov
20
Lec19: Estimation: Confidence Intervals.  (Sections 8.1,8.2,8.5)
22
Lec20:  Large-Sample Confidence Intervals and Selecting the Sample Size (Sections 8.6, 8.7)
Nov
27
Lec21: Hypothesis Testing: Definition. Statistical Tests (Sections 10.1-10.2)
39
Lec22: Common Large-Sample Test. (Section 10.3)
Dec
4
Lec23: Type II Error Probabilities and Sample Size for the Z Test. p-value. (Sections 10.4, 10.6)
6
Lec24 Small-Sample Hypothesis Testing (Section 10.8). Course Review.


Announcements: 

 
Statistical Applets
This page was updated on December 27th , 2007.