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Statistics (STAT)

Statistics (STAT)
Faculty of Arts and Science

Note: Statistics courses are offered by the Department of Mathematics and Computer Science.

Statistics 1770

Introduction to Probability and Statistics
Credit hours: 3.0
Contact hours per week: 3-0-1
Descriptive statistics and graphical representation. Measure of central tendency and dispersion. Elementary probability. Discrete and continuous random variables. Expectation. Binomial, normal and Student's t-distribution. Large and small sample inference and estimation. Central Limit Theorem.
Prerequisite(s): One of Pure Mathematics 30, Mathematics 30, Mathematics 0500, or [Applied Mathematics 30 and at least 75 percent standing in Athabasca University's Mathematics 101]

Statistics 2200

Survey Design and Analysis
Credit hours: 3.0
Contact hours per week: 3-0-0
Simple random sampling. Stratified sampling. Systematic and cluster sampling. Ratio, regression, and difference estimators.
Prerequisite(s): Statistics 1770

Statistics 2780

Statistical Inference
Credit hours: 3.0
Contact hours per week: 3-0-1
Hypothesis testing. Comparison of variances. Chi-square distribution. Contingency tables. Elementary design of experiments. Random sampling. Analysis of variance. Regression and correlation. Examples to illustrate the theory are drawn from a wide variety of fields.
Prerequisite(s): Statistics 1770
Substantially Similar: Economics 2900

Statistics 3500

Mathematical Probability
Credit hours: 3.0
Contact hours per week: 3-0-0
Sample spaces and the algebra of sets. Kolmogorov axioms for probability. Probability density/distribution functions (pdfs) and cumulative distribution functions (cdfs). Joint and marginal pdfs. Combining and transforming random variables. Moment generating functions (mgfs) and factorial generating functions. Applications to discrete and continuous random variables. Central limit theorem. Order statistics.
Recommended Background: Statistics 2780

Statistics 3510

Mathematical Statistics
Credit hours: 3.0
Contact hours per week: 3-0-0
Estimating parameters and the fitting of probability distributions. Maximum likelihood estimators and the method of moments. Properties of estimators, including unbiasedness, sufficiency, and consistency. Large sample theory for estimators. Concepts and theory of statistical hypothesis testing. Distributions derived from the Normal distribution. Comparing two samples through hypothesis tests and confidence intervals. Analysis of variance and linear regression.
Prerequisite(s): Statistics 3500
Recommended Background: Statistics 2780

Statistics 3700

Design and Analysis of Experiments
Credit hours: 3.0
Contact hours per week: 3-1-0
Basic principles of experimental design. Completely randomized designs. Complete and incomplete block designs. Regression. Analysis of variance and analysis with covariates. Contrasts and multiple comparisons. Factorial models. Random effects and fixed effects. Nested designs, split plot designs and related designs.
Prerequisite(s): One of Statistics 2780 or Economics 2900
Equivalent: Statistics 3850 (Design and Analysis of Experiments) (prior to 2009/2010)

Statistics 3850

Topics in Statistics
Credit hours: 3.0
Contact hours per week: 3-0-0

Statistics 4850

Topics in Statistics
Credit hours: 3.0
Contact hours per week: 3-0-0