33 courses in the 1983–84 Undergraduate Calendar, read from the scanned original. The text comes from OCR, so check the scanned page before relying on a detail.
Prerequisites involving these core courses will be given in terms of the lowest level acceptable (e.g. ‘Prereq: MATH 230b' implies that MATH 2406 is also acceptable but MATH 220b is not).
2. The Faculty of Mathematics has completed the implementation (begun in 1980/81) of curriculum changes in its Linear and Abstract Algebra core courses. MATH 221a/b, 231a/b, 241 a/b, 321a/b, 331a/b, PMATH 341a/b have been phased out and replaced by MATH 224a/b, 234a/b, 244a/b, 324, 334, PMATH 344. Degree requirements involving Algebra courses in this and subsequent calendars will be described in terms of the new courses. Students who have completed the old Algebra sequence will obviously not be expected to retake courses from the new sequence. Students with at least one half-credit in the old sequence who have not completed the entire sequence must seek clarification of their position by contacting the Mathematics Undergraduate Office. Under no circum- Stances, without writien Faculty approval, should students mix courses
fram the old and new Algebra
sequences.
MATHOOO F.W 1C 0.0
Co-op Orientation
MATH 000 is a non-credit orientation course for new Co-op Math students.
STAT 202Elementary Statistics for BiologistsF 2C,1L 0.5
Elementary probability, populations, samples and distributions with biological examples. Methods for data summary and presentation inctuding an introduction to interactive programming. Estimation, hypothesis testing, two-sample techniques and paired comparisons. Contingency tables.
STAT 204Statistics for the Physical Sciences 1F 2C,1L 0.5
Descriptive statistics. Probability, random variables, discrete and continuous distributions. Estimation and hypothesis testing, goodness of fit. For Science students only.
STAT 205Statistics for the Physical Sciences 2W 2C,1L 0.5
Linear regression. Introduction to the design of experiments. Completely randomized and randomized block designs. Analysis of variance. Nonparametric statistics.
STAT 210Applied Probability and StatisticsF,W 3C,1T 0.5
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.
STAT 221Introduction to Statistical Methods 2F,W,S 8C,1T 0.5
Tests of significance, maximum likelinood estimation and large sample theory; estimation and testing in the normal distribution. Correlation, regression and the method of least squares.
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.
Introduction to designed experiments. Basic experimental designs. Factorial arrangement of treatments. Confounding and fractional replication. Selected topics.
Summary statistics. Transformation of data. Plotting techniques. Probability plots. Analysis of residuals. Random number generation techniques. Outliérs
* in regression and analysis of variance
data. W-statistics and tests for normality. Computational techniques in multiple unweighted and weighted regression.
STAT 442Statistical Methods for Business and IndustryF 2C,1T 0.5
The decision problem. Bayesian and classical analyses. Acceptance sampling. Sequential procedures. An introduction to the statistica! aspects of quality control.
STAT 450Estimation and Hypothesis TestingF,S 3C 0.5
Discussion of generai inference problems under the headings of point and interval estimation, hypothesis testing, and decision theory. Large sample normal tikelihoods, maximum liketihood estimation, theory of UMV estimation, least squares, Neyman- Pearson theory of hypothesis testing. Prereq: STAT 330.
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.
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.