Not all courses described in the Course and Program Catalogue are offered each year. For a list of course offerings in 2017-2018, please consult the class search website.

For general registration information, please visit students.usask.ca.

As of 2005-2006, certain course abbreviations have changed. Students with credit for a course under its former label may not take the relabeled course for credit.

The following conventions are used for course numbering:

- 010-099 represent non-degree level courses
- 100-699 represent undergraduate degree level courses
- 700-999 represent graduate degree level courses

The following term designations are used:

- 1 - Term 1 only
- 2 - Term 2 only
- 3 - Term 3 only
- 1&2 - Term 1 and 2
- 1/2 - Either Term 1 or Term 2
- P - Phases (Medicine and Dentistry)
- Q - Quarters (Veterinary Medicine)

The following instructional code designations are used:

- L - Lecture
- P - Practicum/Lab
- S - Seminar/Discussion
- C - Clinical Service
- R - Reading
- T - Tutorial

Please use the following form to look up courses and find detailed information on course prerequisites, corequisites, and other special notes. To view all 100-level courses in a subject, select a Subject Code and type 1% in the Course Number field. (200-level = 2%, etc.)

### Results

**STAT 103.3 — 1/2(3L)**

Elementary Probability

An elementary introduction to the concepts of probability, including: sets, Venn diagrams, definition of probability, algebra of probabilities, counting principles, some discrete random variables and their distributions, graphical displays, expected values, the normal distribution, the Central Limit Theorem, applications, some statistical concepts.

**Prerequisite(s):**Mathematics B30 or Foundations of Mathematics 30 or Pre-Calculus 30.

**Note:**Credit will not be granted for STAT 103 if it is taken concurrently with or after STAT 241, STAT 242, STAT 245, STAT 246, PLSC 214, GE 210, COMM 207, PSY 234 or SOC 325. Please refer to the Statistics Course Regulations in the Arts & Science section of the Course and Program Catalogue.

**STAT 241.3 — 1/2(3L-1P)**

Probability Theory

Laws of probability, discrete and continuous random variables and their distributions, moments, functions of random variables and their distributions, Central Limit Theorem.

**Prerequisite(s):**MATH 110 and 116.

**STAT 242.3 — 2(3L-1P)**

Statistical Theory and Methodology

Sampling theory, estimation, confidence intervals, testing hypotheses, goodness of fit, analysis of variance, regression and correlation.

**Prerequisite(s):**MATH 110, 116 and STAT 241.

**Note(s):**Students may receive credit for only one of STAT 242, 244, 245, or 246. Please refer to the Statistics Course Regulations in the Arts & Science section of the Course and Program Catalogue.

**STAT 244.3 — 1/2(3L-1P)**

Elementary Statistical Concepts

Statistical concepts and techniques including graphing of distributions, measures of location and variability, measures of association, regression, probability, confidence intervals, hypothesis testing. Students should consult with their department before enrolling in this course to determine the status of this course in their program.

**Prerequisite(s):**A course in a social science or Mathematics A30 or Foundations of Mathematics 30 or Pre-Calculus 30.

**Note(s):**Students may receive credit for only one of STAT 242, 244, 245, or 246. Please refer to the Statistics Course Regulations in the Arts & Science section of the Course and Program Catalogue.

**STAT 245.3 — 1/2(3L-1P)**

Introduction to Statistical Methods

An introduction to basic statistical methods including frequency distributions, elementary probability, confidence intervals and tests of significance, analysis of variance, regression and correlation, contingency tables, goodness of fit.

**Prerequisite(s):**One of MATH 100, 104 (formerly 101), 110, 121, 123, 125, or STAT 103.

**Note(s):**Students may receive credit for only one of STAT 242, 244, 245, or 246. Please refer to the Statistics Course Regulations in the Arts & Science section of the Course and Program Catalogue.

**STAT 246.3 — 1/2(3L-2P)**

Introduction to Biostatistics

An introduction to statistical techniques with emphasis on methods particularly applicable to biological and health sciences. Topics include: descriptive statistics, estimation and hypothesis testing, linear and logistic regression, contingency tables, life tables, and experimental design. Computerized data analysis will be an essential component of the labs.

**Prerequisite(s):**Mathematics B30 and BIOL 120 and 121 (formerly BIOL 110) or permission of the department.

**Note:**One of MATH 104 (formerly MATH 101), MATH 110 or STAT 103 is recommended but not essential. Students may receive credit for only one of STAT 242, 244, 245, or 246. Please refer to the Statistics Course Regulations in the Arts and Science section of the Course and Program Catalogue.

**STAT 298.3 — 1/2(3L)**

Special Topics

Offered occasionally by visiting faculty and in other special situations to cover, in depth, topics that are not thoroughly covered in regularly offered courses.

**STAT 299.6 — 1&2(3L)**

Special Topics

Offered occasionally by visiting faculty and in other special situations to cover, in depth, topics that are not thoroughly covered in regularly offered courses.

**STAT 341.3 — 1/2(3L-1P)**

Probability and Stochastic Processes

Random variables and their distributions; independence; moments and moment generating functions; conditional probability; Markov chains; stationary time-series.

**Prerequisite(s):**STAT 241.

**STAT 342.3 — 1(3L-1P)**

Mathematical Statistics

Probability spaces; conditional probability and independence; discrete and continuous random variables; standard probability models; expectations; moment generating functions; sums and functions of random variables; sampling distributions; asymptotic distributions. Deals with basic probability concepts at a moderately rigorous level.

**Prerequisite(s):**MATH 225 or 276; STAT 241 and 242.

**Note:**Students with credit for STAT 340 may not take this course for credit.

**STAT 344.3 — 1/2(3L-1P)**

Applied Regression Analysis

Applied regression analysis involving the extensive use of computer software. Includes: linear regression; multiple regression; stepwise methods; residual analysis; robustness considerations; multicollinearity; biased procedures; non-linear regression.

**Prerequisite(s):**STAT 242 or STAT 245 or STAT 246.

**Note:**Students with credit for ECON 404 may not take this course for credit.

**STAT 345.3 — 1/2(3L-1P)**

Design and Analysis of Experiments

An introduction to the principles of experimental design and analysis of variance. Includes: randomization, blocking, factorial experiments, confounding, random effects, analysis of covariance. Emphasis will be on fundamental principles and data analysis techniques rather than on mathematical theory.

**Prerequisite(s):**STAT 242 or STAT 245 or STAT 246.

**STAT 346.3 — 1/2(3L-1P)**

Multivariate Analysis

The multivariate normal distribution, multivariate analysis of variance, discriminant analysis, classification procedures, multiple covariance analysis, factor analysis, computer applications.

**Prerequisite(s):**MATH 266, STAT 241, and one of STAT 344 or STAT 345.

**STAT 348.3 — 1/2(3L-1P)**

Sampling Techniques

Theory and applications of sampling from finite populations. Includes: simple random sampling, stratified random sampling, cluster sampling, systematic sampling, probability proportionate to size sampling, and the difference, ratio and regression methods of estimation.

**Prerequisite(s):**STAT 242 or STAT 245 or STAT 246.

**STAT 349.3 — 1/2(3L-1P)**

Time Series Analysis

An introduction to statistical time series analysis. Includes: trend analysis, seasonal variation, stationary and non-stationary time series models, serial correlation, forecasting and regression analysis of time series data.

**Prerequisite(s):**STAT 241, and STAT 344 or 345.

**STAT 398.3 — 1/2(3S)**

Special Topics

Offered occasionally by visiting faculty and in other special situations to cover, in depth, topics that are not thoroughly covered in regularly offered courses.

**STAT 399.6 — 1&2(3S)**

Special Topics

Offered occasionally by visiting faculty and in other special situations to cover, in depth, topics that are not thoroughly covered in regularly offered courses.

**STAT 442.3 — 2(3L-1P)**

Statistical Inference

Parametric estimation, maximum likelihood estimators, unbiased estimators, UMVUE, confidence intervals and regions, tests of hypotheses, Neyman Pearson Lemma, generalized likelihood ratio tests, chi-square tests, Bayes estimators.

**Prerequisite(s):**STAT 342.

**STAT 443.3 — 2(3L-1P)**

Linear Statistical Models

A rigorous examination of the general linear model using vector space theory. Includes: generalized inverses; orthogonal projections; quadratic forms; Gauss-Markov theorem and its generalizations; BLUE estimators; Non-full rank models; estimability considerations.

**Prerequisite(s):**MATH 266, STAT 342, and STAT 344 or 345.

**STAT 498.3 — 1/2(3S)**

Special Topics

Offered occasionally by visiting faculty and in other special situations to cover, in depth, topics that are not thoroughly covered in regularly offered courses.

**STAT 499.6 — 1&2(3S)**

Special Topics

Offered occasionally by visiting faculty and in other special situations to cover, in depth, topics that are not thoroughly covered in regularly offered courses.

**STAT 812.3 — 1/2(3L)**

Computational Statistics

This course is about computational techniques used in statistical inference. Topics will be selected from: computer arithmetic, Monte Carlo methods for statistical research, optimization methods for maximum likelihood estimation, numerical methods for Bayesian inference, Bayesian analysis using BUGS, bootstrap methods, matrix computations for linear models, and others. This course also serves as a tutorial on a statistical programming language, such as R or Matlab, with examples from statistical inference.

**Prerequisite(s):**STAT 342, STAT 344, and STAT 442 or by permission of the instructor.

**Note:**Students with credit for STAT 846: Special Topics in Probability and Statistics; Special Topics in Computational Techniques in Statistics; and Special Topics in Computational Statistics may not take this course for credit.

**STAT 834.3 — 1/2(3L)**

Advanced Experimental Design

The theory of experimental design, including randomization theory, construction of block designs and Latin squares, factorial designs, and optimal design theory.

**Prerequisite(s):**Undergraduate courses in design and analysis of experiments, such as (STAT 345 or equivalent), mathematical statistics (STAT 342 or equivalent), and linear algebra (MATH 266 or equivalent) or permission of instructor.

**STAT 845.3 — 1/2(3L)**

Statistical Methods for Research

Statistical methods as they apply to scientific research, including: Experimental design, blocking and confounding, analysis of multifactor experiments, multiple regression and model building.

**Prerequisite(s):**STAT 242 or 245 or permission of the department.

**STAT 846.3 — 1/2(3L)**

Special Topics in Probability and Statistics

Topics will be related to recent developments in statistics and probability (multivariate statistics, time series, experimental design, non-parametric statistics, etc.) of interest to the instructor and students.

**Note:**Students may take this course more than once for credit, provided the topic covered in each offering differs substantially. Students must consult the Department to ensure that the topics covered are different.

**STAT 848.3 — 1/2(3L)**

Multivariate Data Analysis

A survey of methods for analyzing discrete and continuous multivariate data. Includes; Log-linear models, logistic regression, canonical correlation, discriminant analysis, cluster analysis, MANOVA, factor analysis.

**Prerequisite(s):**COMM 395, STAT 345 and STAT 845 or permission of the department.

**STAT 850.3 — 1(3L-1S)**

Mathematical Statistics and Inference

An overview of mathematical methods used in theoretical statistics with particular emphasis on inference. Will cover general probability distributions, generating functions, limit theorems, likelihood concepts, exponential families, decision theory, Bayesian and frequentist paradigms for estimation and testing, asymptotic theory.

**Prerequisite(s):**Undergraduate courses in mathematical statistics and inference, such as STAT 342 and STAT 442.

**STAT 851.3 — 1/2(3L-1S)**

Linear Models

A rigorous development of the general linear model, using vector space theory. Generalized inverses, orthogonal projections, quadratic forms, Gauss-Markov theorem, estimability.

**Prerequisite(s):**An undergraduate course in mathematical statistics (STAT 342), linear algebra (MATH 266), and STAT 344 or 345.

**STAT 898.3**

Special Topics

Offered occasionally in special situations. Students interested in these courses should contact the department for more information.

**STAT 899.6**

Special Topics

Offered occasionally in special situations. Students interested in these courses should contact the department for more information.