36 courses in the 1981–82 Undergraduate Calendar, read from the scanned original. The text comes from OCR, so check the scanned page before relying on a detail.
Course Descriptions
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Elementary probability, populations, samples and distributions with biological examples. Methods for data summary and presentation including an introduction to interactive programming..Estimation, hypothesis testing, two-sample techniques and paired comparisons. Contingency tables.
Prereq: None
N.B. Stat 202 is for Science Students only.
Descriptive statistics. Probabitity, random variables, discrete and continuous distributions. Estimation and hypothesis testing, goodness of fit.
Prereq: None
N.B.: Stat 204 is for Science Students only.
Linear regression. introduction to the design of experiments. Completely randomized and randomized block designs. Analysis of variance. Nonparametric statistics.
Prereq: Stat 202 or 204
N.B.: Stat 205 is for Science Students only.
Laws of probability. Discrete and continuous random variables. Uniform, binomial, Poisson, normal distributions. Sampling from a normal population. Student-t, chi-square, F distributions. Estimation and hypothesis testing. Simple linear regression.
Prereq: Math 110a/b
N.B. This course is for students in Mechanical Engineering, and is cross listed in Management Sciences as M Sci 21.
Course Descriptions Statistics
Probability theory; discrete and continuous random variables, expectation.
Prereq: Math 120a/b, one of CS 116, CS 118, CS 140 N.B.: Stat 220 is not open to Honours Mathematics students. Credit will be given for only one of Stat 220, 230.
Tests of significance, maximum likelihood estimation and large sample theory; estimation and testing in the normal distribution. Correlation, regression and the method of least squares. Prereq: Stat 220
N.B.: Stat 221 is not open to Honours Mathematics students. Credit will be given for only one of Stat 221, 231.
The laws of probability, discrete and continuous random variables, expectation, central limit theorem. Prereq: Math 120a/b
N.8.: Credit will be given for only one of Stat 220, 230 .
Estimation, tests of significance, probability plots. Contingency tables, norma! distribution theory, simpte linear regression.
Prereq: Stat 230
N.B.: Credit will be given for only one of Stat 221, 231.
The design of surveys of human or natural populations for research and planning. How to take a representative sample; efficient estimation of population quantities and sample size determination; ways of reducing response bias.
Prereq: An introductory half course in statistics. N.B.: Stat 300 cannot be taken for credit toward a BMath degree.
A second course in statistics for the non-specialist. Estimation and hypothesis testing related to the normal distribution. Moment generating functions. Maximum likelihood theory. Bivariate normal distribution.
Prereq: Stat 221 or equivalent
N.B.: Credit will be given for only one of Stat 330.
Review of Normal, t, Chi-squared and F distributions and their applications. Introduction to the design of experiments. Analysis of variance, multiple linear regression. , Prereq: Stat 221 or the equivalent.
N.B.: Credit will be given for only one of Stat 331, 357.
Introduction to survey sampling of populations. Elementary sampling designs. Efficiency comparisons for sampling designs and estimation procedures.
Prereq: Stat 221 or the equivalent
N.B.: Credit will be given for only one of Stat 332, 454.
Review of basic probability. Generating functions. Theory of recurrent events. Markov chains, Markov processes, and their applications.
Prereq: Stat 230 or Stat 220/221
Discrete Markov processes. Renewal theory. Branching processes. Stationary processes. Selected topics.
Prereq: Stat 333 or consent of instructor
Continuous random variables; moments and moment generating function; distribution of t, chi-squared, and F, and their applications. Large sample theory. Prereq: Math 230a/b, Stat 231 or consent of instructor.
N.B.: Credit will be given for only,one of Stat 330, 350.
The multivariate normal distribution, its properties and uses; quadratic forms and Cochran’s theorem; multiple regression; introduction to the analysis of variance.
Prereq: Stat 350, Math 234a/b
N.B.: Credit will be given for only one of Stat 331, 357.
Course Descriptions ; 401 Statistics
The requirements for a good experimental design Prior to the accumulation of data. The concepts of randomization, replication and experimental errors as applied to basic designs; the completely randomized block and latin square designs. Analysis of variance. Introduction to factorial designs. Prereq: Stat 337 or 351 or consent of instructor. N.B.: Credit will be given for only one of Stat 430, 452.
Factorial experiments, confounding, fractional replication. Applications of designs. Incomplete block designs. Analysis of covariance.
Prereq: Stat 430
N.B.: Credit will be given for only one of Stat 437, 452.
Summary statistics. Transformation of data. Plotting techniques. Probability plots. Analysis of residuals. Random number generation techniques. Outliers in regression and analysis of variance data. W-statistics and tests for normatity. Computational techniques in multiple unweighted and weighted regression.
Prereq: Stat 331 or 351, and an ability to programme in FORTRAN.
The decision problem; Bayesian and classical analyses; acceptance sampling; sequential procedures; an introduction to the statistical aspects of quality control.
Prereq: Stat 221, Stat 330 recommended.
N.B.: Credit will be given for only one of Stat 442, 450.
Survey and analysis of typical statistical models in Economics and the Social Sciences. Review of regression analysis. Extensions of the linear model. Specification errors. Time series and forecasting. Prereq: Stat 331 or 351.
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Discussion of general inference problems under the headings of point and interval estimation, hypothesis testing, and decision theory. Large sample normal likelihoods, maximum likelihood estimation, theory of UMV estimation, least squares, Neyman-Pearson theory of hypothesis testing. Prereq: Stat 350
N.B.: Credit will be given for only one of Stat 442, 450.
Logic of tests of significance; exact tests and confidence intervals; normal approximations accurate for small samples and relationship to the normality of the likelihood function. Introduction to problems involving more than one parameter. Prereq: Stat 450 or consent of instructor
Logical requirements of designed experiments. Design and analysis of basic complete designs with fixed effects, random effects, or both. Analysis of covariance. Latin squares. Applications.
Prereq: Stat 331 or 351 or consent of instructor N.B.: Credit will be given for only one of Stat 430/431, 452.
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Introduction to sample theory and practice. Elementary sampling and designs and estimation procedures. Statistical inference in survey sampling. Interrelationships between survey sampling and the design of experiments.
Prereq: Stat 331 or 351
N.B.: Credit will be given for only one of Stat 332, 454.
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Prereq: Stat 333/4 or consent of instructor N.B.: May or may not be offered 1981-82
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The design of surveys of human or natural populations for research and planning. How to take a representative sample; efficient estimation of population quantities and sample size determination; ways of reducing response bias.
Prereq: An intreductory half course in statistics N.B.: Stat 500 is intended for senior undergraduates and graduate students in faculties other than Mathematics, It cannot be taken for credit towards a Mathematics degree.
May or may not be offered in 1981-82
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