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STAT
STATISTICS
See also "Mathematics".
Students should note that in the Science Faculty the minimum acceptable grade in a course which is
required by a particular program or is used to meet a prerequisite, is a "C". Any student who fails to
attain a "C" or better in such a course must repeat the course (at the next regular session) until a grade
of "C" or better is attained. Students will not be eligible for graduation until such deficiencies are
removed. The only exception will be granted for a single course with a “D” grade that is a normal part of
the final year of that program, and is being taken for the first time in the final year
STAT 2*** courses may not be taken by students who have passed a higher level STAT course.
See Courses -> Saint John or Fredericton -> Standard Course Abbreviations in the online undergraduate calendar for
an explanation of abbreviations, course numbers and coding.
STAT 2043
Statistics for Social Scientists I.
3 ch (3C)
Topics from survey statistics: simple random sampling, systematic sampling, question
composition, scaling techniques. Topics from basic statistics: descriptive statistics,
estimating/testing means, standard deviations, proportions, paired data versus two
independent samples, chi-square tests. Prerequisite: Successful completion of at least one year
of program. NOTES: Credit can be obtained in only one of STAT 2043, 2253, 2263, 2264, or
2593. Not to be taken for credit by CS, MATH or STAT majors.
STAT 2253
Introductory Statistics For Forestry Students
3 ch (2C 2L)
Emphasis on applications to forestry and biology, using a statistical package. Graphical and
numerical summaries of data; Populations, samples, sampling techniques; Normal distribution;
Estimation and tests for means, medians, proportions; Individual versus mean behaviour;
Matched pairs, independent samples, analysis of variance; Regression; Chi-squared tests for
categorical data. NOTE: Credit can be obtained for only one of STAT 2043, 2253, 2263, 2264, or
2593.
STAT 2263
Statistics for Non-Science Majors
3 ch (3C)
An introductory course in statistics. Experiments, sampling, basic descriptive statistics.
Probability, random variables, Normal distribution. Confidence intervals for means and
proportions. Tests of hypotheses. Paired samples vs. two independent samples. Contingency
tables. Regression, correlation. Introduction to analysis of variance. Examples drawn from the
health sciences. Use of a statistical computer package. Prerequisite: New Brunswick
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Mathematics 112 GA (Geometry and Applications) and New Brunswick Mathematics 112 FR
(Functions and Relations), or equivalent. Note: Credit can be obtained for only one of STAT
2043, 2253, 2263, 2264, or 2593.
STAT 2264
Statistics for Biology
3 ch (3C)
An introductory course in statistics. Probability, Bayes' Theorem, applications of probability to
genetics, random variable, expectation, binomial and normal random variables, confidence
intervals for means and proportions, prediction intervals, tests of hypotheses, paired data
versus two independent samples, brief introduction to analysis of variance, regression,
correlation, contingency tables, examples drawn from medicine and biology, use of a statistical
computer package. Prerequisite: A minimum grade of 60% in New Brunswick Advanced
Mathematics (120), or equivalent. Note: Credit can be obtained for only one of STAT 2043,
2253, 2263, 2264, or 2593.
STAT 2593
Probability and Statistics for Engineers
3 ch (3C)
Probability spaces: combinatorial probability; conditional probability and independence.
Random variables: discrete distributions; continuous distributions; expectation, variance, and
covariance; linear combinations. Statistics: descriptive and graphical statistics; sampling
distributions. Inference: point estimation; confidence intervals; hypothesis tests; paired data
designs; two sample inference. Prerequisite: MATH 1013. Note: Credit can be obtained for only
one of STAT 2043, 2253, 2263, 2264, or 2593.
STAT 3043
Statistics for Social Scientists II
3 ch (3C)
Topics from survey statistics: stratified sampling; cluster sampling. Questionnaires:
construction, administration, interpretation and reporting. Topics from basic statistics:
regression; one way and two way analysis of variance. Prerequisite: STAT 2043. Not to be taken
for credit by CS, MATH or STAT majors. Note: Credit can be obtained for only one of STAT 2253,
2263, 2264, 2593, or 3043.
STAT 3083
Probability and Mathematical Statistics I
3 ch (3C)
The first half of a two-part sequence covering various topics in probability and statistics. This
course provides an introduction to probability theory and the theory of random variables and
their distributions. Probability laws. Discrete and continuous random variables. Means,
variances, and moment generating functions. Sums of random variables. Joint discrete
distributions. Central Limit Theorem. Examples drawn from engineering, science, computing
science and business. Prerequisite: MATH 1013. Note: Credit can be obtained in only one of
STAT 2593 or 3083.
STAT 3093
Probability and Mathematical Statistics II
3 ch (3C)
The second half of a two-part sequence covering various topics in probability and statistics. This
course provides an introduction to essential techniques of statistical inference. Samples and
statistics versus populations and parameters. Brief introduction to method of moments and
maximum likelihood. Tests and intervals for means, variances and proportions (one and twosample). Multiple regression, residual plots. Analysis of variance, brief introduction to
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experimental design. Chi-squared tests. Examples drawn from engineering, science, computing
science and business. Use of a statistical computer package. Prerequisite: STAT 3083. Students
with exceptional standings in STAT 2593 may seek permission from the instructor.
STAT 3303
Methods of Operations Research I
3 ch (3C)
Linear programming, the simplex method, post optimal analysis, derivation of dual theorem,
game theory, network analysis. Various applications will be discussed. Prerequisite: MATH 2003
or equivalent and 2213.
STAT 3313
Methods of Operations Research II
3 ch (3C)
A continuation of STAT 3303. The topics include: dynamic programming, integer programming,
nonlinear programming, inventory theory, and forecasting. Prerequisite: STAT 3303.
STAT 3373
Elementary Experimental Design
3 ch (3C)
Randomization, one and two way classifications. Latin squares, factorial experiments, nesting,
incomplete blocks, linear regression. Emphasis on applications. Extensive use of a statistical
computer package. Prerequisite: STAT 2263, 2264, 2593, or 3093, MATH 1503 or 2213.
STAT 3383
Introduction to Stochastic Processes (A)
3 ch (3C)
Exact contents may vary from year to year, e.g.: counting processes and Poisson processes;
renewal processes (discrete); finite state Markov chains; stationary covariance processes.
Prerequisite: STAT 2593 or STAT 3083 and one of MATH 2013 or MATH 2213.
STAT 4043
Sample Survey Theory
3 ch (3C)
Simple random sampling; stratified sampling; systematic sampling; multi-stage sampling;
double sampling; ratio and regression estimates; sources of error in surveys. Prerequisite: STAT
3093.
STAT 4053
Regression Analysis
3 ch (3C)
Likelihood ratio tests; distribution of quadratic forms, noncentral chi square, noncentral F;
independence of quadratic forms; linear models, model classification; general linear hypothesis
of full rank, Gauss-Markov theorem, normal equations, tests of hypotheses; polynomial models;
orthogonal polynomials; regression models; experimental design models; estimable functions.
Prerequisite: STAT 3093 and one of MATH 1503 or 2213.
Logistic regression models for binary response variables, log-linear models for contingency
tables, Poisson regression models for count response variables, multinomial regression models
for categorical response variables, cumulative logit and continuation-ratio regression models
for ordinal response variables, model selection, some special topics in generalized linear
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models. Emphasis will be on computer implementation and applications in social sciences,
psychology, education, medicine, sciences and engineering.
Prerequisite: STAT 3093 or the permission of the instructor.
STAT 4083
Introduction to Multivariate Statistics
3 ch (3C)
Multivariate normal distribution; estimation of the mean vector and covariance matrix; partial
and multiple correlation coefficients; multiple regression; the T2 statistics; tests of hypotheses;
discriminant analysis; principal components; factor analysis. Prerequisites: 6 ch of Calculus, 3 ch
of Linear Algebra and STAT 3093.
STAT 4100
Honours Project
6 ch [W]
Statistics Honours students must complete a project under the supervision of a faculty member.
The project is to include a written report and an oral presentation. Prior to being admitted into
STAT 4100, the student must have been admitted to the Honours Program and have submitted
an acceptable project proposal to the department. Normally students would begin preparation
and research for the project during their third year of study, submit the proposal by October of
their fourth (final) year of study, and complete the written and oral presentation by the end of
the winter term, to graduate in May of that year. Honours students in an interdepartmental
program with statistics may choose to complete their honours project in statistics.
STAT 4293
Statistical Computing
3 ch (3C)
Introduction to the R statistical computing language. Use of data frames and lists. Simulation of
data. Advanced graphics. General Statistical routines. Coding of new procedures. Bootstrapping
and cross-validation. Prerequisites: STAT 2593 or both of STAT 3083, 3093.
STAT 4303
Stochastic Models In Operations Research
3 ch (3C)
Discusses various models involving decision making under uncertainties. Topics include:
queuing theory, Markovian decision process, reliability and quality control, simulation. Corequisite: STAT 3303. Prerequisites: STAT 2593 or STAT 3083.
STAT 4333
Queuing Theory (A)
3 ch (3C)
Introduction, queuing models. Single and multiserver queuing models. Analysis of queuing
models using differential difference equation, generating functions, distribution of busy
periods. Transient behaviour, introduction to bulk queuing and other queuing models.
Prerequisite: STAT 2593 or 3083.
STAT 4443
Time Series Analysis and Applications (A)
3 ch (3C)
Discrete time series and stochastic processes; autocorrelation and partial correlation functions;
white noise; moving averages; autoregressive, mixed and integrated processes; stochastic
models, fitting, estimation and diagnostic checkup; forecasting; forecasting in seasonal time
series; applications would include problems from Economics, Engineering, Physics. Prerequisite:
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STAT 3093.
STAT 4903
Independent Study in Statistics
3 ch
Advanced topic in Statistics to be chosen jointly by student, advisor, and Department Chair.
May be taken for credit more than once. Title of topic chosen will appear on transcript.
Prerequisite: Permission of Department.
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