.
?
S.87-63
SIMON FRASER UNIVERSITY
MEMORANDUM
To: ?
Senate ?
From: J.W.G. Ivany
Chair, SCAP
Subject: Faculty of Science ? Date: November 19, 1987
Department of Mathematics and
Statistics
Reference SCUS 87-34; 87-51;
Reference SCAP 87-29; 87-54
Action undertaken by the Senate Committee on Academic Planning/Senate
Committee on Undergraduate Studies gives rise to the following motions:
S
Motion 1: that Senate approve and recommend approval to the Board of
Governors as setforth in S.87-63 the introduction of Honors,
Major and Minor Program options in statistics, and
Introduction ?
to ?
Statistics ?
for
Social Research
Applied ?
Probability Models
Selected Topics in
Probability
and ?
Statistics
Selected Topics in
Probability
and ?
Statistics
Generalized Linear and
Nonlinear Modelling
Statistical
?
Quality Control
Directed Studies in Probability and
Statistics"
New courses STAT 103-3
STAT 280-3
STAT 290-3
STAT 390-3
STAT 402-3
STAT 440-3
STAT 495-3
Motion 2: ?
that Senate approve and recommend approval to the Board of
Governors as set forth in S.87-63
.
?
New course MATH 447-4 Coding Theory
Label change to STAT 1O3
Label change to STAT 102-3
Label and number change to
STAT 270-3
Change of title, description,
prerequisites and label
to STAT 302-3
Change to prerequisites
Change of title, description,
prerequisites and label
and number to STAT 330-3
Label and number change to
STAT 380-3
Change prerequisites and label and number to STAT
410-3
Label and number change to
STAT 420-3
Change of title, description,
prerequisites and label
and number to STAT 430-3
Change of title, description,
prerequisites and label
and number to STAT 450-3
Label and number change to
STAT 460-3
Label and number change to
STAT 480-3
Label and number change to
STAT 490-3
S
- ?
MATH
101-3
- ?
MATH
102-3
- ?
MATH
272-3
- ?
MATH
302-3
- ?
MATH 3093
- ?
MATH 372-3
- ?
MATH
387-3
- ?
MATH
304-3
- ?
MATH
33
-. ?
MATH
404-3
- ?
MATH 472-3
- ?
MATH 475-3
- ?
MATH 487-3
- ?
MATH 479-3
Acting under delegated authority, SCUS approved the following changes to
existing courses as set out in S.87-63
S
is
- ?
001
0 ?
Proposal for Chan
g es
in
Statistics Offerings
The following changes are being proposed in response to recent developments in the
field of statistics, in the employment market, and in related programs of study at SFU.
These developments include
(i)
the emergence of the generalized linear model as a powerful new tool for
handling a broad array of statistical inference problems,
(ii)
the extraordinary demand for quality assurance specialists who are
needed to keep North American industries competitive,
(iii)
the development of a program in manufacturing systems by the School of
Engineering Science, and
(iv) the maturation of our offerings in statistics into an identifiable
undergraduate program.
The changes are summarized as follows,:
(1) the upgrading of the three service courses, MATH 302, 304, and 404,
(2) minor alterations to MATH 272,
• ?
(3) ?
major alterations to MATH 372 and 472,
(4)
the relabelling of certain MATH courses with the abbreviation code,
STAT,
(5) the creation of three new courses, STAT 280, 402, and 440,
and
(6) the delineation of formal program options in statistics.
fl
-9-
002
6) ?
Program Options in Statistics
?
is
With the maturing of the discipline of statistics, many universities are
now offering formal undergraduate programs in the subject. A degree program
containing substantial training in statistical methodology and reasoning,
related mathematics and computing science, and detailed knowledge of a
potential field of applications provides a solid foundation for a wide variety
of careers as well as for graduate research. The following program proposals
are designed to recognize formally the concentration of courses already being
selected by many of our undergraduates.
-10-
• ?
_____
Statistics Major and Honours Options
Students majoring or taking honors in Mathematics with the statistics option
for a B.A. degree are subject to the general regulations of the Faculty of Arts.
Students majoring or taking honorsin Mathematics with the statistics option for a
B.Sc. degree are subject to the general regulations of the Faculty of Science. In
each case, students following these
l
options will be required by the Department of
Mathematics and Statistics to obtain credit for the following courses:
(1)
Lower Division Mathematics: MATH 151 (or 154 or 157), 152 (or 155 or 158),
232, 242, 251, and 252.
(2)
Lower Division Statistics: STAT 270 and 280.
(3)
Lower Division Computing: CMPT 101 or 102 or 103, or equivalent evidence of
competence in computer programming.
(4)
Upper Division Mathematics/Mathematical Computing: MATH 310 and MACM 316.
(5)
Upper Division Probability and Statistics: STAT 330, 430, 450, and at least
three of STAT 402, 410, 42 440 and 460
(6)
Upper Division - Auxiliary
Concentration:
At least 15 upper division credit
hours in some specific field other than probability and statistics,
. ?
mathematics, or computing science. These courses are to be approved by a
departmental advisor.
(7)
In addition, faculty requirements stipulate that at least two other upper
division courses be taken in Mathematics, Statistics, or Mathematics/Computing
Science. These would normally be selected from the remaining options listed
in (5) or the following list'.
Other recommended mathematics courses: MATH 243, 308, 309, 313, 320, 322,
343, 408, 419, 426, 438, 439, 443, and 487.
(8)
In addition to requirements (1) through (6) for a Major, candidates for an
Honors degree in Mathematics with the statistics option will be required to
obtain credit for MATH 320, 322, 426, 438, and 487, all of the courses listed
under (5) above, and three 4lditional upper division courses labelled MATH,
STAT, or MACM.
L
-U-
- ?
004
Statistics Minor Option
Candidates for a Minor in Mathematics with the statistics option are subject
to the general regulations of the faculty in which they are registered. In
addition, they must
(i)
obtain credit for
MATH 151 (or 154 or 157), 152 (or 155 or 158), 232, 251, and STAT 270,
and
(ii)
obtain credit for at least 5 of the following courses:
STAT 330, 380, 402, 410, 420, 430, 440, 450, and 460, and MATH 487.
(This will normally include STAT 330, 430, and 450.)
S
0
-2-
005
The proposed changes to courses are summarized in the following table:
Existing Course* ?
New Course Label and Title
MATH 101-3 ?
STAT 101-3 Introduction to Statistics A
MATH 102-3 ?
STAT 102-3 Introduction to Statistics B
MATH 272-3 ?
STAT 270-3 Introduction to Probability and Statistics
?
STAT 280-3 Applied Probability Models
STAT 290-3 Selected Topics in Probability & Statistics
MATH 302-3
?
STAT 302-3 Analysis of Experimental and Observational Data
MATH 304-3* ?
STAT 410-3 Statistical Analysis of Sample Surveys
MATH 372-3* ?
STAT 330-3 Linear Models in Applied Statistics
MATH 387-3 ?
STAT 380-3 Introduction to Stochastic Processes
STAT 390-3 Selected Topics in Probability & Statistics
STAT 402-3 Generalized Linear and Nonlinear Modelling
MATH 404-3*
?
STAT 430-3 Statistical Design and Analysis of Experiments
MATH 4723*
?
STAT 450-3 Intermediate Statistical Theory
MATH 473-3
?
STAT 420-3 Nonparametric Statistics
MATH 475-3 ?
STAT 460-3 Decision Analysis and Bayesian Inference
STAT 440-3 Statistical Quality Control
MATH 479-3
?
STAT 490-3 Selected Topics in Probability & Statistics
STAT 495-3 Directed Studies in Probability & Statistics
MATH 487-3 ?
STAT 480-3 Probability Theory
.
?
* This symbol signifies a course that is proposed to undergo major revisions.
The new prerequisite structure is summarized by the following diagram.
101
?
102
?
270
302 ?
280
?
330
402 ?
380 ?
440 ?
402, 410
420, 430
480
?
450, 460
0
-3-
- ?
006
Detailed Pro p
osals and Rationale
1) ?
MATH 302, 304, and 404.
MATH 302 has been a successful service course. Nonetheless, its gradual
evolution in response to student interest has rendered the title and calendar
description somewhat outdated.
We are therefore proposing the following editorial changes:
From: MATH 302-3 Statistical Methods.
Nonparametric statistics, analysis of variance and related topics which
are intended to help students understand the uses of statistics in
experimental research.
Prereciuisites: STAT 101 or 102 or 272 (or MATH 272) or ARC 376 or BIJEC
232 (formerly 332).
(Mathematics major and honors students may not use this course to
satisfy the required number of semester hours of upper division
Mathematics courses. However, they may include the course to satisfy
the total number of required hours of upper division credit.)
To: ?
STAT 302-3 Analysis of Experimental and Observational Data.
The standard techniques of multiple regression analysis, analysis of
variance, and analysis of covariance, and their role in experimental
research.
Prereciuisite: STAT 101 or 102 or 270 (or MATH 272) or ARC 376 or BUEC
232 (formerly 332). Students who have obtained credit for STAT 330 are
not permitted to take STAT 302 for further credit.
(Mathematics major and honors students may not use this course to
satisfy the required number of semester hours of upper division
Mathematics courses. However, they may include the course to satisfy
the total number of required hours of upper division credit.)
MATH 304 and 404 were originally designed as service courses in sample
surveys and experimental design. To broaden the scope of offerings while
still conserving limited teaching resources, we also made them available to
mathematics majors. As service courses, they have not been very successful.
MATH 304, for example, provides useful information to graduate students in the
social sciences planning to run their own surveys, but for a variety of
reasons (including the fact that they cannot receive graduate credit), few of
these students actually take the course. Most of the students in MATH 304 and
404 have in reality had rather strong mathematical backgrounds, and have found
the courses not very challenging. The problem has been compounded in the case
of MATH 304 by the lack of any suitable text. By upgrading the prerequisite
for MATH 304 and increasing the number to a 400-level, we are able to adopt a
challenging, well-written text, often used at the graduate level.
MATH 404 will also have its prerequisite upgraded. By insisting upon
STAT 330 (a modernized version of MATH 372) as a prerequisite, we can cover
the material in advanced experimental design presented in the last half of the
innovative text we are recommending for STAT 330.
0
S
-4-
- ?
oo'i
W ?
Proposal: (a) Change the number and prerequisites for MATH 304 as follows:
From: MATH 304.
Prerequisite: ?
One course in Statistics or Probability; e.g. MATH 101
or 102, or PSYC 201.
To: ?
STAT 410
Prerequisite: ?
STAT 330.
(b)
Change the number, title, and calendar description for MATH 404 as
follows:
From: MATH 404-3 Experimental Design
Design of experiments; factorial experiments; block designs and
confounding; analysis of variance; analysis of covariance; regression
and multiple regression.
Prere q uisite: ?
MATH 302 or 372. Permission will be given to students from
other departments, with suitable backgrounds.
To: ?
STAT 430-3 Statistical Design and Analysis of Experiments
An extension of the designs discussed in STAT 330 to include more than
one blocking variable, incomplete block designs, fractional factorial
designs, and response surface methods.
Prere q uisite: ?
STAT 330 (or MATH 372).
(c)
Change the detailed descriptions to the appended versions.
2)
MATH 272. In response to both the increasing numbers of engineering science
students in MATH 272 and the general interest in quality assurance, we are
proposing minor alterations to the detailed description (but not the calendar
outline) for this course. A proposed new version is attached. The central
changes are (a) inclusion of basic control charts, and (b) a change of
textbook.
3)
MATH 372 and 472. For MATH 372 (to be relabelled STAT 330) we propose a shift
in emphasis toward experimentation and model building. The course will still
introduce students to the fundamentals of statistical inference. It should
provide a solid foundation for more detailed study of complex experimental
designs in MATH 404 (STAT 430), and statistical theory in MATH 472 (STAT 450)
and MATH 475 (STAT 460). (The recommended text for MATH 404 [STAT 430] is the
same as that for MATH 372 [STAT 330]. Each course would cover a different
half of the same book.) The existing version of STAT 450 (MATH 472) would
conflict heavily with the proposed new versions of STAT 330 and 430.
Furthermore, our existing offerings do not touch on two very important areas -
- nonlinear regression and generalized linear models. For these reasons, we
are proposing that the title and calendar descriptions to MATH 372 and 472 be
changed as follows:
-5-
008
From: MATH 372-3 Introduction to Probability and Statistics II
Techniques of estimation and hypothesis testing, one-sample and two-
sample tests. Introduction to analysis of variance, regression and
correlation.
To:
?
STAT 330-3 Linear Models in Applied Statistics
Standard statistical inference procedures for analyzing experimental and
survey results. Statistical model building. Foundations of
experimental design.
From: MATH 472-3 Linear Models in Statistics
Linear models, analysis of variance and covariance, multiple regression,
introduction to the design of experiments.
To: ?
STAT 450-3 Intermediate Statistical Theory
Methods for constructing tests
•
and estimators, weighted least squares,
nonlinear regression, and the generalized linear model.
A proposed new detailed description is attached.
4)
To aid students in finding the courses in probability and statistics offered
by this department, it is proposed that the abbreviation code MATH be changed
to STAT on each of the following courses: MATH 101, 102, 272, 302, 304, 372,
404, 472, 473, and 475. Where appropriate the statement would be appended,
STAT xyz may not be taken for further credit if credit has already been
obtained for MATH uvw. Furthermore, new course numbers are being proposed for
selected topics (STAT 290, 390, and 490) and directed studies (STAT 495)
courses in probability and statistics.
5)
New courses STAT 280, STAT 402 and STAT 440.
Following are detailed rationales for these course proposals. Course proposal
forms and detailed descriptions appear in the appendix.
0
5.
Date:
6---
Dean
?
Chairman, SCTJS
r..
Appendix
B3
SENATE COMMITTEE
ON UNDERGRADUATE STUDIES
?
.
?
Oo
COURSE PROPOSAL FORM
l. Calendar Information
Department:
Mathematics & Statistics
Abbreviation Code:
STAT
Course
Number:
103
Credit Hours:______ Vector:________
Title of Course:
?
Introduction to Statistics for Social Sciences
Calendar Description of Course:
A
course similar to
STAT
101 (formerly
MATH
101) but directed to students in the
social sciences.
Nature of Course
L
sEC
'T & R
£ -
?
__
Prerequisites (or special instructions):
?
See entry level requirements. Students with
credit for ARC. 376, BtJEC 232 (formerly 332) or STAT 270 (formerly MATH 272 and
MATH 371) may not subsequently receive credit for STAT 103. Students with credit
for STAT 101, STAT 102 MATH 101 or MATH 102 may not take
STAT
103 for further credit.
What course (courses), it any, is being dropped from the calendar if this course is
approved:
2. Scheduling
How frequently will the course be offered?
?
Once per year.
Semester in which the course will first be offered?
?
Fall 1988. ?
-
Which of your present faculty would be available to make the proposed offering
possible: ?
D.
Eaves, R. Lockhart, R. Routledge, M. Stephens,
T.
Swartz, K.L. Weldon
?
' ?
Objectives of the Course
• To introduce the material of
STAT
101 (formerly MATH 101) in a way that will be
perceived as directly relevant to students with majors in the social sciences, and
• to encourage active participation in the course by these students. The Department
of Mathematics and Statistics will maintain an advisory committee which will allow
any department which requires or recommends this course to have a continuing
opportunity to provide input on course presentation.
4. Budgetary and Space Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual.
Space
Equipment
SCUS 73-34bz- (When completing this form, for instructions see Memorandum SCUS
73-34a.
Attach course outline).
STATISTICS 103-3
?
010
Introduction to Statistics for Social Research
Prere q
uisite: B.C. High School Algebra 11 (or equivalent). Students lacking
this background may take the non-credit Basic Math Course offered through
Continuing Studies, AQ 6050. Students with a grade of P in B.C. High
School Algebra 11 should take the Math Assessment Test. Students with
credit for STAT 101, STAT 102, SrA1t04/
P
1½ATH 101, MATH 102, ARC. 376-5,
BUEC 232-3 (formerly BUEC 332-3) or STAT 270 (formerly MATH 272 and MATH
371) may not subsequently receive credit for STAT 103-3.
Textbook: Please refer to the Departmental Textbook List, available outside
of the Math & Stats. General Office TLX 10512.
******
Aimed at a non-mathematical audience, this courses discusses procedures
that are most commonly used in research in the social sciences. The rationale
for these procedures is explained in detail, but the use of mathematical
formulas is kept to a minimum. STAT 103 is a satisfactory prerequisite for
MATH 302.
1.
The Design of a Statistical Study
The two major design types, controlled experiments and observational
studies, are discussed, with special emphasis on the limitations of
each. The practical necessity of observational studies in social
sciences research is discussed.
2.
Descri ptive
Statistics
The following methods of summarizing the information in large data sets
are introduced: histograms and other graphs, averages, standard
deviations, and the normal approximation. Applications to summary of
social and political surveys.
3.
Correlation and Regression
The correlation coefficient is introduced as a measure of the strength
of association between two quantities; the regression line, as a graph
of averages. Deviations from this line are discussed. Use of these
techniques in formulating causal hypotheses based on studies in social
sciences.
4.
Probabilit
Methods are presented for computing the probabilities of chance
occurrences. The binomial formula is stressed. Examples are introduced
which explain how probability is used to model the unpredictability of
human responses.
5.
Chance Variability
Fallacious interpretations of "The Law of Averages" are brought to
light, and the predictable patterns that do indeed emerge in repetitions
of chance experiments are discussed. The use of aggregation as a method
for concentrating information from widely variable measurements, such as
are encountered in social surveys.
(over) •
Appendix
L4:3
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
-
?
Oil
COURSE PROPOSAL FORM
1. Calendar Information
?
Department:
Mathematics and Statistics
Abbreviation Code: STAT
.
Course Number: 280
Credit Hours:
_L
Vector:
3-1-0
Title of Course:
?
Applied Probability Models
Calendar Description of Course: Review of elementary probability models. Conditional
probability and conditional ex
p
ectation. Fitting and testing adequacy of models.
Applications to production management and quality control. Introduction to simple
Markov chains, Poisson processes, inventories and queues. Reliability models
including lifetime analysis and circuit configuration.
Nature of Course
For students with a good mathematics background and an interest in applications.
Prerequisites (or special instructions):
STAT 270 (or MATH 272).
What course (courses), if any, is being dropped from the calendar if this course is
approved: none-
2. Scheduling
How frequently will
the course be offered? Once per year.
Semester in which the course will first be offered? 1989-3
.
?
Which of your present faculty would be available to make the proposed offering
?
possible:
Drs. Eaves, Lockhart, Routledge, Stephens, Swartz, Weldon
3. Objectives
of the Course
(1)
Preparation for STAT
380
and STAT
440.
(2)
Satisfy Core-B requirements in Engineering Science.
(3)
Provide an introduction to the applications of probability theory to
mathematically-inclined students.
4. Budgetary and Space Requirements (for information only)
What additional resources will be required in
the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
5. Ap2
ro
v a l
?
OCTG6W
Date: ?
Department Chairman
?
Dean ?
Chairman.,
IEIIZIII
SCUS
SCUS 73-34b:- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
- ?
012
STATISTICS 280-3 ?
Applied
Probability Models
1.
A review of Elementary Probability Models: binomial, negative binomial,
hypergeometric, Poisson, geometric, exponential, gamma, normal and F-
distributions. Nonparametric probability models.
2.
Conditional Probability and Conditional Expectation: modelling dependence
with conditional models, simplification of dependence by conditioning,
assessment of model fit (residual analysis, probability plotting, and
goodness-of-fit tests).
3.
Introduction to Markov Chains. Random walks. Applications to simple models
for inventories and queues. Birth-death processes. Steady state assessment.
4.
Introduction to lifetime analysis. Exponential and related lifetime models.
Hazard functions. Poisson process and relating counting processes. Weibull
distribution. Reliability.
5.
Modelling serial correlation. Moving averages and autoregressive models.
Predictive and explanatory models. Phenomena of serial correlation.
Each topic is illustrated with examples from many fields. The emphasis would be on
the use of simple models to assist in the explanation of complex real-world
phenomena. The modelling process would be discussed in detail.
Textbook: AN INTRODUCTION TO STOCHASTIC MODELLING,
by H.M. Taylor and S. Karlin, 1984
0
-6-
013
Rationale for STAT 280
STAT 280 (Applied Probability Models) is proposed as a new course to follow
STAT 270 (MATH 272) (Introduction to Probability and Statistics) and to precede STAT
380 (MATH 387) (Introduction to Stochastic Processes) and STAT 440 (Statistical
Quality Control). The course would satisfy the following functions:
(1)
To introduce applications of probability models.
(2)
To improve the preparation for STAT 380.
(3)
To provide access to the material of STAT 440.
These points are elaborated as below:
(1)
Students of probability theory seldom learn of its practical utility
until graduate school or later. Courses at the undergraduate level have tended to
emphasize definitions and properties of models but not their discovery or
identification in practical contexts. This proposed course emphasizes these latter
aspects.
(2)
STAT 380 (Introduction to Stochastic Processes) covers fairly advanced
probability models and includes challenging problems. The sophistication it
S
requires has made it overly difficult for all but the most able students. STAT 280
would provide a better background for STAT 380 and allow more material to be covered
in STAT 380.
(3)
Students in STAT 280 would spend considerable time studying several
probability models of use to people working in industrial quality control, process
improvement, and reliability assessment. This background would permit the
development of more insight in STAT 440.
C
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
?
Appendix 83
COURSE PROPOSAL FORM
?
- ?
0
1. Calendar Information
?
Department:
Mathematics & Statistics
S
Abbreviation Code:
STA T
Course Number:
290
?
Credit Hours:
?
Vector: 3-1-0
Title of Course:
?
Selected Topics in Probability and Statistics
Calendar Description of Course:
Topics in areas
of
probability and statistics not covered in the regular
undergraduate curriculum
of
the department.
Nature of
course
?
Lecture/Tutorial
Prerequisite. (or special instructions):
Dependent on the topic covered.
What course (courses), if any, is being dropped from the calendar if this course is
approved:
2. Scheduling
How frequently will the course be offered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
3.
Ob j ectives of the Course
The proposed relabelling
of
courses in probability and statistics with the
code, 'STAT', would otherwise leave the department with no means
of
offering
a selected topics course in this field.
4.
Budgetary and Space Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual.
Space
Equipment
S. Approval
?
OCT06 1987
Date,
Chairman, SCUS
8CU8 73-34bs- (When completing this form for instructions see Memorandum SCUS 73-34a.
Attach course outline).
S
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
?
Appendix B3
COURSE PROPOSAL FORM
?
-
?
Oi i
0
1. Calendar Information
Abbreviation
Code:_
STAT
Course Number:
390
?
Department:
Mathematics & Statistics
?
Credit Hours:
3 ?
Vector:
3-1-0 -
Title of Course:
?
Selected Topics in Probability and Statistics ?
Calendar Description
of Course:
Topics in areas of probability and statistics not covered in the regular
undergraduate curriculum of the department.
Nature of Course
?
Lecture/Tutorial
Prerequisites (or special instructions):
Dependent on the topic covered.
What course (courses), if any, is being dropped from the calendar if this course is
approved:
2. Scheduling
Bow frequently will
the course beoffered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
0
Objective, of the Course
The proposed relabelling of courses in probability and statistics with the
code, 'STAT', would otherwise leave the department with no means of offering
a selected topics course in this field.
4. Budgetary and Space Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual.
Space
Equipment
S. Approval ?
Date:
Chairman, $CUS
BCUS 73-34bs- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
5.
Approval
Date:
an,
SCUS
SCUS 73-34b:- (When completing this form, for instructi
Attach course outline).
see Memorandum SCUS 73-34a.
JperIuJ'
03
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
COURSE PROPOSAL FORM
?
- ?
016
1.
Calendar Information
?
Department: Mathematics and Statistics
Abbreviation Code:
STAT Course Number: 402 Credit
Hours:
3 Vector: 3-1-0
Title of Course:
?
Generalized Linear and Nonlinear Modelling
Calendar Description of Course: A skills-oriented unified approach
to a broad array
of non-linear regression modelling methods including classical regression, logistic
regression, probit analysis, dilution assay, frequency count analysis, ordinal-type
responses, and survival data.
Nature of Course Lecture/Tutorial
Prerequisites (or special instructions):
STAT 302 or STAT 330.
What course (courses), if any, is being dropped from the calendar if
this course is
approved:
MATH 404
2. Scheduling
How frequently will the course be offered?
Once per year.
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
Drs. Eaves, Lockhart, Routledge, Stephens, Swartz, Weldon.
3.
Objectives of the Course
To provide training to advanced undergraduates and to graduate students in
other departments, in nonlinear regression modelling of a wide variety
of common data types.
4.
Budgetary and S
p ace Re
q
uirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
S
S
STATISTICS
402-3 ?
Generalized Linear and
Nonlinear Modelling
01?
.
Note: This course extends the concepts, methods and approach of STAT 302-3 to cover
a wide variety of types of outcome data. It employs a modern unified approach
to a broad array of nonlinear regression problems.
1.
Brief Review of Fundamental Background.
2.
Overview: Empty model, link function, simple examples of structuring a mean
value vector with link function and design matrix, and of structuring variance
with a variance function; iterated reweighted least squares estimation.
3.
Examples from exponential-type likelihood models: Normal, including classical
linear regression and other links; Poisson, including log-linear regression;
Binomial, including logit, probit, and dilution assay. Examples allowing
overdispers ion.
4.
Other Examples.
5.
Inference: The variance-covariance matrix of the estimated regression vector
and confidence intervals for linear predictors, fitted values, other relevant
estimated quantities; comparative evaluation of models, deviance, Pearson
statistic, residuals.
6.
Logistic Regression.
7.
Contingency tables and log-linear models.
8.
Ordinal-type outcome: Proportional odds model, proportional hazards model.
9.
Survival data.
(or as much of the above as time permits)
Primary Reference:
An Introduction to Statistical Modelling
by Dobson
Chapman and Hall, 1983
Other Reference: Sections 1 through 6 of:
The CLIM System, Release 3, Manual
Baker and Nelder
Numerical Algorithms Group, 1978
0
-7-
018
Rationale for STAT 402
?
.
A relatively non-mathematical two-course modern statistical methods sequence
has long been offered (302-404). This concept remains sound, but a second course
(402) in such a service sequence now needs to strive to rely more on intuition than
on mathematics, and to exploit recent developments in nonlinear regression in such a
way as to cover a much wider variety of outcome data types.
Emphasis will be on practical skills with several computing packages, and on
conceptual unity. It is an essential component of skill training for data-oriented
scientists in the 80's.
0
.
Chairman, SCUS
5. approval
Date: -
A ppendix B
SENATE COMMITTEEON UNDERGRADUATE STUDIES
COURSE PROPOSAL FORM
?
0i
1. Calendar Information
?
Department:
Mathematics and Statistics
Abbreviation Code:
STAT
Course Number:
440 ?
Credit Hours: 3 Vector: 3-1-0
Title of Course:
-
Statistical
.
Jli tyControl
Calendar Description of Course:
Desi
g
n and implementation of control charts and alternatives, process capability
analysis, acceptance sampling procedures, systerri reliability models, hazard
analysis, and related economic considerations.
Nature of Course Lecture/Tutorial
Prerequisites (or special instructions):
?
STAT 280, and STAT 330 (or MATH 372).
What course (courses), if any, is being dropped from the calendar
if this course is
approved: none.
2.
Scheduling
How frequently will the course be offered? Once per
year.
Semester in which the course will first be offered? 1989-.1
Which of your present faculty would be available to make the proposed offering
possible:
Drs. Eaves, Lockhart, Routled g
e, Stephens, Swart, and Weldon
3.
Objectives of the Course
To
p
rovide a thorou
g
h background in the theory of quality control and
reliability theory. Students with this training would be in a strong
position to contribute to the competitiveness of industries.
4. Buds ?
(for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
SCUS 73-34b:- (When completing this f
?
e Mern ' :urandurri SCUS 73-34a.
Attach course outline).
STATISTICS 440-3 ?
02U
?
•
Statistical Quality Control
This course is designed for students with credit in STAT 280 and 330. Using
this as a base, students will study in depth the design and use of (i) control
charts for monitoring production processes, (ii) acceptance sampling schemes, and
(iii) experiments that can be conducted in a search for improved production
processes. If time permits, these ideas will be supplemented by a discussion of
system reliability. By the end of the course, students should be well prepared to
handle questions on these topics on the Quality-Engineer-in-Training examination set
by the American Society for Quality Control.
-8-
.
Rationale for STAT 440
North American industries are being forced to adopt new procedures for
quality control. These involve a variety of activities including, for example,
the increased use of statistical charts for monitoring established production
processes, experimental manipulations of production processes to reduce output
variation, and the modelling of reliability for complex products. Our existing
courses in statistics train students in the related, general theory. This
proposed course will delve into the specific problems confronting quality
assurance specialists. The demand for people with such training is forecast to
continue to be very strong for the foreseeable future. We plan to use this
course, and related modifications to our programs, to prepare students for
careers in this expanding section of the job market. We intend to monitor the
impact of these changes with a view to developing a program in quality assurance
in the near future.
.fll'1.
q
gg
S. Approval
?
Date,
Chairman, SCUS
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
?
Appendix B3
COURSE PROPOSAL FORM
?
021
1. Calendar Information
S
Department: Mathematics & Statistics
Abbreviation Code:
STAT
Course
Number:495
Credit Hours:
3
?
Vector:__________
Title of Course:
?
Directed Studies in Probability and Statistics
Calendar Description of Course:
Independent reading or research in consultation with the supervising instructor.
Nature of Course
?
Independent study and consultation.
Prerequisites (or special instructions):
Written permission of the Department Undergraduate Studies Committee.
What course (courses), if any, is being dropped from the calendar if this course is
approved:
2. Scheduling
How frequently will the course be offered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
0
3. Objectives of the Course
The proposed relabelling of courses in probability and statistics with the
code, 'STAT', would otherwise leave the department with no means of offering
a directed studies course in this field.
4. Budgetary and Space Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual.
Space
Equipment
SCUS 73-34bz- (When cc*npl.ting this form, for instructions see Memorandum
SCUS
73-34a.
Attach course outline).
Appendix B3
SENATE
COMMITTEE ON UNDERGRADUATE STUDIES
(.
1
?
Trf,r+
4
?
COURSE
PROPOSAL FORM
?
022 ?
•
Department:
Mathematics & Statistics
Abbreviation Code: MATH Course Number:.
447
?
Credit Hours:4
?
Vector:
4-0-0
Title of Course: CODING THEORY
Calendar Description of Course:
An introduction
to the
theory and practice of error-
correcting codes. Topics will include finite fields, polynomial rings, linear, and
non-linear codes, BCH codes, convolutional codes, majority logic decoding, weight
distribution of codes, and bounds on the size of codes.
Nature of Course Lecture
Prerequisites (or special instructions):
Math 232; Math 439 is recommended.
What course (courses), if any, is being dropped from the calendar if this course is
approved: ?
None.
2. Scheduling
How
frequently will the course be offered? Once
a
year.
Semester in which the course will first be offered?
Which
of your present faculty would be available to make the proposed offering
possible:: Alspach, Godsil, Heinrich, Hell, Brown
Objectives
of the Course
To introduce students to the most important families of codes and
tPré
?
?
algorithms used in decoding them; to indicate the connections
?
'coding
theory to other branches of mathematics.
4. Budgetary and Space Requirements (for information only)
What additional resources will be required in the following areas:
.
Faculty
Staff
Library
Audio Visual
?
None.
Space
Equipment
5.
Date: *
9, ?
/^^&
Chairman
• ?
PIAR'171987
Dean ?
Chairman, SCUS
SCUS
73-34):- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
0-
?
MATH 447-4 (4-0-0) CODING THEORY
?
023
COURSE DESCRIPTION
This course is intended to be an introduction to the theory and practice
of error-correcting codes. The following selection of topics is
representative:
1)
elementary algebra, finite fields
2)
linear and non-linear codes
3)
cyclic codes
4)
BCH codes
5)
convolutional codes
6)
majority logic decoding
7)
weight distributions of codes; codes and designs
8)
bounds on the size of codes
PREREQUISITES: MATH 232;
Math 439 is recommended.
TEXTBOOK: ?
Richard E. Blahut: Theory and Practice of Error Control
L
?
Codes, Addison Wesley (1983)
FURTHER REFERENCES:
Shu Lin and Daniel
J.
Costello: Error Control Coding,
Prentice-Hall (1983)
F.J. MacWilliams and N.J.A. Sloane: The Theory of
?
Error -Correctin.g Codes, North Holland (1977)
J.H. Van Lint: Introduction to Coding Theory, Springer
(Graduate Texts in Mathematics 86) (1982)
Vera Pless: Introduction to the Theory of Error-
?
Correcting Codes, Wiley-Interscience (1982).
Proposed new course MATH 447 CODING THEORY.
RATIONALE: Such a course will be useful to graduate
engineers and rratheuiat cs majors. Universities
with strength in Cornbinatorics and Optimization
frequently have such a course. A supporting
letter from Prof.
Jim Cavers, Engineering
Science, is enclosed. Also enclosed find the
course proposal form and the extended course
outline.
I—]
avers
?
........
SiMON FRASER UNIVERSITY
?
U
MIMORANDUM
024
Svbj.d.....
Date.
.JY.cPr..i..T)............
This is a
very belated
response to the course proposal you sent me
on May 30. I didn't
realize
that you needed a written response or I
would have replied some time ago.
?
.
We are quite enthusiastic about your offering a coding theory
course. The material is essential to design of digital coninun
.
icat ion
systems, but is not usually offered in any depth in a typical
undergraduate engineering program. Engineers frequently discover its
importance only during
their first
system design.
We plan to give graduate credit for engineers in our Master's
program taking this course, on the grounds- that engineering programs
at other universites usually offer the
material only at the graduate
level. ? -
I would expect it to be a fairly popular course, given the number
of communications oriented companies in the Lower Mainland. I hope
you would consider offering it in the late afternoon or evening,
to make it more accessible to our part-time students.
cc D. George
B. Clayman
0
Chairman, SCUS
.
Chan g e of Label Only 4:
Appendix
B3
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
?
INFORMATION
?
COURSE PROPOSAL FORM ?
FOR
Calendar Information
?
Department: Mathematics and Statistics
025
Abbreviation Code: STAT Course Number: 101
?
Credit Hours: 3 ?
Vector: 3-0-1
Title of Course: ?
Introduction to Statistics
1
4Pfl
<.i
" '
Calendar Description of Course:
Nature of Course
Prerequisites (or special instructions):
Add the statement, "Students with credit for MATH 101 may not take STAT 101
for further credit."
What course (courses), if any, is being dropped from the calendar if this course is
approved: MATH 101
2. Scheduling
How frequently will the course be offered?
I
Semester in which the tourse will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
3.
Objectives of the Course
4. Budgetary and S
p ace Re q
uirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
?
-
Equipment
5. Approval
?
OCT 06 IN?
Date:
SCUS 73-34b:- (When completing this form, for instructions see. Memorandum SCUS 73-34a.
Attach course outline).
** Change of Label Only **
?
Appendix
B3
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
FOR INFORMMION
COURSE PROPOSAL FORM
1.
Calendar Information ?
Department: Mathematics and Statistics
0210
Abbreviation Code: STAT Course Number: 102 Credit Hours: 3 Vector: 3-0-1
Title of Course: ?
Introduction to Statistics
,
1 flO-'
tb
Calendar Description of Course:
Nature of Course
Prerequisites (or special instructions):
Add the statement, "Students with credit for MATH 102 may not take STAT 102,
for further credit."
What course (courses), if any, is being dropped from the calendar if this course is
approved: MATH 102
2.
Scheduling
How frequently will the course be offered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
3.
Objectives of the Course
4. Bud g etar
y
and S
p
ace Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Stff
Library
Audio Visual
Space
Equipment
5.
Approval ?
OCT 06 9?
Date:
44cf
Department Chairman
--------------------
?
Dean
-------------------------
Chairman, SCUS
S
SCUS 73-34b:- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
COURSE PROPOSAL
FORM
?
FOR INFORMATION
a.
Calendar Information
?
Department: Mathematics and Statistics
027
Abbreviation Code: STAT Course Number: 270
?
Credit Hours: 3 ?
Vector: 3-1-0
Title of Course: ?
Introduction to Probabilit
y
and Statistics
Calendar Description of Course:
Nature of Course
Prerequisites (or special instructions):
Add the statemnt, Students with credit for MATH 272 may not take
STAT 270 for further credit."
What course (courses), if any, is being dro
pp
ed from the calendar if this course is
approved: MATH 272
2.
Scheduling
How frequently will the course be offered?
Semester in which the course will first be offered?
. ?
Which of your present faculty would be available to make the proposed offering
possible:
3.
ObjectivespJ the Course
The course label is being changed as part of a major relabelling of probability
and statistics courses. The course title is to be altered editorially.
(The Roman Numeral 'I' is being dropped because the title of the sequel, MATH 372
i4
to be changed.)
4.
Bgetary and Space Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
5.
pjoval
?
OCT s 181
Date:
Departm nt Chairman
?
Dean ?
Chairman, SCUS
SCUS 73-34b:- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
?
-
FOR INFORMATION
STATISTICS 270-3
?
028
Introduction to Probability and Statistics
This course introduces students to probability theory and its applications to
statistics, management science, reliability, quality control, insurance, computing
science, etc. Students who do reasonably well in mathematics are encouraged to take
the stream beginning with STAT 270 instead of STAT 101 or 102. This is particularly
important for students considering taking a concentration of courses in mathematics
and statistics. The foundations of statistical inference procedures are established
in each of these courses; however, only STAT 270 has sufficient mathematical content
to prepare students for the entire sequence of probability and statistics courses
offered by the Department of Mathematics and Statistics.
DETAILED CONTENTS (not necessarily covered in this order)
1.
Chance Phenomena and Randomization
Examples of naturally arising chance phenomena and the role of
randomization in experimental design will be discussed.
2.
Laws of Probabilit
Methods will be developed for computing probabilities of chance
occurrences. These will include laws for probabilities of combinations of
simple events, and combinatorial arguments for use when all outcomes are
equally likely.
3.
Paradoxes in Probability
Common misconceptions and myths about chance events in everyday life
will be scrutinized. This will involve special attention to the notion of
conditional probability. The paradoxes will specifically include inspection
and waiting-time paradoxes.
4.
Probability Distributions and Random Variables
Histograms and density curves, means, variances, and standard deviations
will be introduced. The following special distributions will be developed:
uniform, binomial, negative binomial, geometric,hypergeometric, Poisson,
gamma, exponential, normal. Other distributions may be discussed, time
permitting. These will be applied to such fields as engineering, risk theory,
quality control, reliability, and the interpretation of scientific
experiments.
5.
Laws of Expectation and Standard Error
Rules for finding the expectation and standard error for sums of
independent random variables will be developed.
0
FOR INFORMATIOI
6.
Transformations of Random Variables
Methods for finding the distribution of a transformation of a single
random variable will be discussed.
?
AC)
- ?
1.16
7.
The Sam p
ling Behaviour of an Average
The average of a randomly drawn sample is subject to chance
fluctuations. Predictable patterns that exist in these chance fluctuations
will be derived. Moment generating functions will be used to aid in the
derivation. The often misunderstood "law of averages" will be examined in
light of the formal law of large numbers and central limit theorem.
8.
Making Decisions Under Uncertainty
Standard procedures for assessing the accuracy of a sample estimate of
an average and a proportion along with methods for making decisions under
uncertainty will be introduced in an informal way. The discussion will
specifically include applications to basic control charts and acceptance
sampling schemes, and confidence intervals and hypothesis tests for a single
mean or proportion.
Textbook: AN INTRODUCTION TO MATHEMATICAL STATISTICS AND ITS APPLICATIONS
by R. Larsen and M. Marx
Prentice-Hall Publishers, 1981.
0
Appendix B3
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
COURSE PROPOSAL FORM ?
FOR INFORMATION
1.
Calendar
Information
?
Department: Mathematics and Statistics
Abbreviation Code:
STAT
Course Number:
302
Credit
Hours: - Vector: (3-O-4)
Title of Course:
?
Anal y
sis of Ex
p
erimental and Observational Data
Calendar Description of Course:
The standard techniques of multiple regression analysis, analysis of
variance, and analysis of covariance, and their role in scientific research.
Prerequisites: STAT 101 (or MATH 101) or STAT 102
Nature of Course ?
(or MATH 102) or STAT 270 (or MATH 272) or ARC
376 or BUEC 232 (formerly 332). Students with credit
Prerequisites (or special
instructions): for MATH 302 may not take STAT 302 for further
credit.
[Mathematics major and honors students may not use
this course to satisfy the required number of semester
hours of upper division Mathematics courses.
However, they may include the course to satisfy the
total number of required hours of upper division credit.)
What course (courses), if any, is being dropped from the calendar if this course is
approved:
MATH 302.
2.
Schedilincj
How frequently will the course be offered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
3.
Objectives of the Course
4.
Bud
g etar y
and Space Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
5.
Approval
Date:
Departm t Chairman ?
Dean ?
Chairman, SCUS
SCUS 73-34b:- (When ccsmpletinq this form, for instructions see Memorandum SCUS 7334a.
Attach course outline).
STATISTICS 302-3 ?
FOR INFORMATION
ANALYSIS OF EXPERIMENTAL AND OBSERVATIONAL DATA ?
Ii 31
NOTE: This course is designed for the non-mathematician. It is intended to follow
STAT 101-3 or STAT 102-3. Some mathematical notation is introduced but mathematical
results are not proved. Instead the results are explained heuristically so that the
student can understand the rationale of the techniques commonly used in applied
statistics. The exposition will use many examples from both the social and natural
sciences.
TOPICS
1.
The course begins with a review of STAT 101, STAT 102; the review will cover
and extend the mathematical notation introduced in STAT 102, and used less
extensively in STAT 101.
2.
Introduction to Regression Analysis
Simple regression, regression and causality, assumptions of linear regression,
measuring adequacy of assumptions, estimation of error variance, inferences
concerning slope and intercept, inferences concerning the simple regression
line, interpretation of estimated regression lines, prediction with regression
lines.
3.
Correlation and its Relationshi p
to Regression
Definition of the correlation coefficient, r, measures of association, and the
bivariate normal distribution, what r does not measure, estimation and testing
with r.
?
. 4. ?
Analysis of Variance
?
(
One- and two-way analysis of variance, the analysis of variance table and
related tests, fixed and random effects, multiple comparison procedures and
contrasts.
5.
Multiple Regression Analysis
Using more than one independent variable, graphical considerations for this
problem, assumptions, collinearity, estimation of the best regression
equation, analysis of variance table, overall and partial F tests.
6.
The General Linear Model
Multiple Regression and analysis of variance as special cases of the general
linear model. The general procedure for constructing F-tests by fitting
restricted models. Applications to analysis of covariance and comparison of
two regression model.
7.
Correlations: Multi
p
le. Partial and Multiple-Partial
Correlation matrix, multiple correlation coefficient, the multivariate normal
distribution, partial correlation coefficient, F-tests for multiple and
partial correlations.
8.
Analysis of Residuals
• Checking on the assumptions of regression and analysis of variance models,
effects of departures from the assumptions, transformations.
Textbook: APPLIED REGRESSION ANALYSIS
W
?
by D.G. Kleinbaum and L.L. Kupper
PUB: Duxbury, 1978
MAR i
Dean
5. Apro
Date:
**
CHANGE IN
P
REREQUISITE ONLY
?
Appendix 53
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
FOR INFORMATION
I. Calendar Information
Department: Mathematics &
-
?
StatistjcL
032
0
Abbreviation Code: MATH Course
Number:
309 Credit Hours:3
?
Vector:3-1-0
Title of Course: CONTINUOUS OPTIMIZATION
Calendar Description of Course:
(no change)
Nature of course
Prerequisites (or special instructions):
MATH 232 and 251; MATH 308 is recommended.
What course (courses), if any, is being dropped from the calendar if this course is
approved:
2. Scheduling
How frequently will the course be offered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
Objectives
possible:
of the Course
0
4. Budgetary and Space Req
uirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual.
Space
Equipment
S
S
SCUS
scs
73-34bs- (When oonpl.ting this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
A
pp
endix
B3
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
FOR INFORMATION
COURSE fPOSAL FORM
033
0 -
Calendar Information
?
Department:
Mathejtics and Statistics
Abbreviation Code:
STAT
Course
Number: 330 Credit Hours: _. Vector: 3-1-0
Title of Course:
?
Linear Models in Applied Statistics
Calendar Description
of Course:
Standard statistical inference Procedures for analyzing ex
p
erimental and survey
results. Statistical model building. Foundations of experimental design.
Nature of Course
Lecture/Tutorial
Prerequisites (or special instructions):
Math 232, and STAT 270 (or MATH 272). Students with credit for MATH 372
may not take STAT 330 for further credit.
What course (courses), if any, is being dropped from the calendar if this course is
approved: MATH 372-3.
2.
Scheduling
How frequently will the course be offered?
Semester in which the course will first be offered?
• ?
Which of your present faculty would be available to make the proposed offering
possible:
3.
Objectives of the Course
4.
Buetarii
Space Reguirement (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
5. 8p
ploval
Date:
Departm nt Chairman
SCUS 73-34b:- (When completing this form,
Attach course outline).
o
DL
Dean ?
____________________
Chairman, SCUS
for instructions see Memorandum SCUS 73-34a.
Linear Models in Applied Statistics
Scientific method and its implications for statistical method.
1.
034
•
STATISTICS 330
?
FOR INFORMATIOt
Methods for comparing two, treatment means with emphasis on the reference
distributions appropriate in various situations. Independence and serial
correlation.
3. Randomization and blocking: two treatment examples. Methods of analysis and
interpretation of results. Implications for experimental design.
4.
Significance tests and confidence intervals for means variances, proportions,
and frequencies. Introduction to likelihood ratio tests and maximum
likelihood estimation.
5.
Analysis of variance. Comparison of several treatment means. Model
diagnostics.
6. Elementary design of experiments. Randomized blocks and two-way factorial
designs.
7.
Regression Analysis. Multiple regression. Use of regression for analysis of
variance. Analysis of covariance. Model diagnostics.
8. Use of statistical computer packages for regression and analysis of variance
models. Monte Carlo demonstrations in the linear models context.
Textbook: Statistics for Experimenters
Box, Hunter and Hunter
Wiley, 1978.
The material in this course is primarily contained in chapters 1 through 7, and
chapter 14 of the text.
Prere q uisites: Math 232, and STAT 270 (or MATH 272).
.
0
: CHANGE OF LABEL AND PREREQUISITE ONLY :$$:
?
Appendix B
SENATCOMMITTEE
COURSE
ON
PROPOSAL
UNDERGRADUATE
FORM
JflJD
'OR INFORMAT1OI
035
Calendar Information ?
Department:
Mathematics and Statistics
Abbreviation Code:
STAT Course Number: 380 Credit Hours: 3 Vector: 3-1-0
Title of Course:
?
Introduction to Stochastic Processes
Calendar Description of Course:
Nature of Course
Prerequisites (or special instructions):
STAT 280. Students with credit for MATH 387 may not take STAT 380 for further
credit.
What course (courses), if
any, is
being dropped from the
calendar if this course is
approved:
MATH 387.
2.
Scheduling
How frequently
will
the course be offered?
?
•
?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
3.
Objectives of
the Course
The chan g
e is part of a major relabellin g
of probability and statistics courses.
4.
Budgetary and Space Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
5.
approval ?
OCT 06 w
Date:
?
S
-- -- -----------
?
-----
Departm nt Chairman
?
Dean
?
Chairman,
CU
SCUS 73-34b:- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
5. Approval
Date: -
CT P
?i
I Jt7flLih
)
L
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
COURSE PROPOSAL FORM ?
FOR INFORMATION
1.
Calendar Information
?
Department:
Mathematics and Statistics
Abbreviation Code:
STAT Course Number: 410 Credit Hours: 3 Vector: 3-1-0
Title of Course: ?
Statistical Anal
y sis of Sample Surveys
Calendar Description of Course:
An introduction to the major sample survey designs and their mathematical
justification. Associated statistical analyses.
Nature of
Course Lecture/Tutorial
Prerequisites (or
special instructions):
From: One course in statistics or probability
To: STAT 330 (or MATH 372) or permission of the instructor.
Students with credit for MATH 304 may not take STAT 410 for further credit.
What course (courses), if any, is being dropped from the calendar if this course is
approved:
MATH 304.
2.
Scheduling
How frequently will the course be offered?
Once per year.
Semester
in which the course will first be offered?
Whichof your present faculty would be available to make the proposed offering
possible: Drs. Eaves, Lockhart, Routledge, Stephens, Swartz, and Weldon.
3.
Objectives of the Course
To provide training to advanced undergraduates in the design and analysis of
complex sample surveys. Training in this field is a major advantage to graduates
seeking employment with survey agencies such as Statistics Canada.
4. Bud g etary
and Space Re
quirements
(for information only)
What additional resources will be required in the following
areas:
S
Faculty
Staff
Library
Audio Visual
Space
Equipment
Because this course would be offered less frequently than
the course to be deleted, MATH 304, adoption of this proposal
would result in a net saving to the university.
;;ius-----S
SCUS 73-34b:- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
FOR INFORMATION
.
?
STATISTICS 410-3
r
'jJ
"
Statistical Analysis of Sample Surveys
This course develops the statistical theory required for constructing
and analyzing complex sample surveys. Applications to be discussed may include
e.g., the Gallup Poll, market surveys, the Canadian Labour Force Survey, and forest
surveys.
Detailed Description
1.
The Role of Randomization in Sample Surveys: Bias, standard error, and root
mean squared error, survey terminology.
2.
Simple Random Sampling: Using random number generators and tables to take a
simple random sample, the sampling frame, estimating means, totals, and
proportions, the finite population correction factor, confidence limits,
problems with the use of the normal approximation, choosing the sample size.
3.
Stratified Random Sampling: Advantages of stratification, estimating gains in
precision, confidence limits, optimal sample sizes, effects of errors in
calculated stratum sizes and in optimal allocation, stratification after
selection.
?
• 4.
?
Ratio and Regression Estimates: Purpose and examples, bias, standard error,
confidence limits, optimal conditions, optimal allocation, weak dependence on
usual regression assumptions.
5.
Systematic Sampling: A brief survey of the models required to estimate the
variance, and of potential advantages and disadvantages.
6.
Cluster and Multi-Stage Sampling: Purpose and examples, comparison
estimators, equal- vs. unequal-probability sampling, optimal choice of
sampling fractions and probabilities.
7.
Double Sampling: An overview of the role of double sampling in constructing
stratified, ratio, and regression estimates; sampling on two or more
occasions.
Text: Sampling Techni
q
ues, 3rd ed., by W.G. Cochran
0
5. Approval ?
Date:
scu
** CHANGE OF LABEL ONLY :
?
Appendix
53
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
COURSE PROPOSAL FORM
?
FOR INFORMATION
1.
Calendar Information
?
Department:
Mathematics and StatistQ48
?
40
Abbreviation Code:
STAT
Course
Number:
420
Credit Hours: 3
Vector:
3-1-0
Title of Course:
?
Non-Parametric Statistics
Calendar Description of Course:
Nature
of Course Lecture/Tutorial
Prerequisites (or special instructions):
Change to read, "STAT 330 (or MATH 372) or permission of the department.
Students with credit for MATH 473 may not take STAT 420
for further credit."
What course (courses),
if any, is being dropped from the calendar if this course is
approved:
MATH 473.
2.
SchedulinQ
How frequently will the course be offered?
Semester in which the course will first be offered?
Whith of your present faculty would be available to make the proposed offering
possible:
3.
Objectives of the Course
4.
Budgetary and S
p
ace Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
SCUS 73-34b:- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
S
Chairman, SCUS
.** MODIFICATION OF EXISTING COURSE **
?
Appendix B3
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
COURSE PROPOSAL FORM
?
FOR INFORMATION
0
1. Calendar Information
?
Department:
Mathematics & Statistics
Abbreviation Code:_
STAT
Course Number:
430 ?
Credit
Hours:
Title of Course:
?
Statistical Design and Analysis of Experiments
Calendar
Description of Course:
An extension of the designs discussed in STAT 330 to include more than one
blocking variable, incomplete block designs, fractional factorial designs,
and response surfac
.
e methods.
Nature of Course
Prerequisites (or special
instructions): ?
From: MATH 302 or 372 or permission.
To: STAT 330. (or MATH 372).
Students with credit for MATH 404 may not take STAT 430 for further credit.
What course (courses), if any, is being dropped from the calendar if this course is
approved: ?
MATH 404.
2. Scheduling
How frequently will the course be offered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
S
possible:
Objectives of the Course
4. Budgetary
and
Space Requirements (for information only)
What additional resources will
be
required in the following areas:
Faculty
Staff
Library
Audio Visual.
Space
Equipment
5. pproval
?
OCT
Date:
SCUS 73-34bz- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
FOR INFORMATION
STATISTICS 430-3
040
Statistical Design and Analysis of Experiments
1.
Review of blocking and factorial designs.
?
Two-way blocking and Latin Squares.
Fractional factorials. ?
Sequential use of these designs in practical settings.
2. More elaborate designs based on Latin squares and incomplete blocks.
3. Response surface methods. ?
Optimization under uncertainty. ?
Parametrization of
complex phenomena.
4.
Model building: ?
Mechanistic and Empirical models. ?
Introduction to nonlinear
normal error distributions, heterocedastic data, transformations, and weighted
least squares. ?
Use of standard statistical computer packages for non-standard
analyses.
5.
Industrial Process control. ?
Study of variation.
6. Modelling dependence in time series.
Textbook: ?
STATISTICS FOR EXPERIMENTERS
by Box, Hunter and Hunter
PUB: John Wiley and Sons
: MODIFICATION OF EXISTING COURSE
?
Appendix
B3
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
COURSE PROPOSAL FORM
?
FOR INFORMATION
•1. Calendar Information
?
Department:
Mathematics and Statistics
Ot1
Abbreviation Code:
STAT
Course Number:
450
Credit Hours: 3 Vector:
3-1-0
Title of Course:
?
Statistical Theory
Calendar Description of Course:
Methods for constructing tests and estimators, weighted least squares, nonlinear
regression and the generalized linear model.
Nature of Course
Prerequisites (or special instructions):
From: MATH 232 and 372 (or 371).
To: MATH 232, and STAT 330 (or MATH 372).
Students with credit for MATH
472
may not take STAT 450 for further credit.
What course (courses), if any, is being dropped from the calendar if this course is
approved:
MATH 472.
2.
Scheduling
How frequently will the course be offered?
Semester in which the course will first be offered?
S ?
Which of your present faculty would be available to make the proposed offering
possible:
3.
Objectives of the Course
4.
Budgetary and Space Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
5.
Approval
Date:
?
our
0 ?
I'DepartmeIt Chairman ?
?
'f
Dian
?
Chairman, SCUS
SCUS 73-34b:- (When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
STATISTICS 450-3 ?
FOR INFORMATION
•.
Statistical Theory ?
01.112
Methods for constructing tests and estimators, weighted least squares,
nonlinear regression, and the generalized linear model.
Detailed Description
This course explores strategies for constructing new estimation and hypothesis
testing procedures. Emphasis will be placed on using the likelihood function, and
on related least-squares theory for normally distributed errors. These strategies
will be used to derive methods for extending regression techniques to models
involving unequal variances, nonlinearity, and non-normal error distributions.
1.
Distribution Theory
Joint, marginal, and conditional densities. Multivariate changes of
variables.
2.
Maximum Likelihood Estimation.
Motivation, alternatives, properties, computations.
3.
Likelihood Ratio Tests.
Neyman-Pearson theory and applications to simple hypotheses, extensions and
large-sample approximations, relation between hypothesis tests and confidence
intervals.
4. The Geometr y
of Ordinar y Least Squares.
Least squares and orthogonal projections; the multivariate normal density and
its relationship to t- F- and chi-squared-distributions; applications to
analysis-of-variance.
5.
Unequal Variances.
Weighted least squares and the Gauss-Markov theorem, relation to maximum
likelihood estimates, iterative schemes.
6. Nonlinear Regression.
Mechanistic model building, transformations, nonlinear least squares,
computations, hypothesis tests and confidence intervals.
7.
Generalized Linear Models for Fre
q uenc y
Data.
Models involving Poisson and related error distributions, likelihood ratio
tests for frequency data, log-linear models, introduction to GLIM.
0
CHANGE OF LABEL ONLY **
?
Appendix 53
?
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
COURSE PROPOSAL FORM
?
FOR INFORMATION
A1
s
Department: ?
C)
•
1. Calendar Information
?
Mathematics & Statis
Abbreviation
Coda:
STAT Course Number:460
?
Credit Hours:3
?
Vector: 3-1-0
Title of Course:
?
Decision Analysis and Bayesian Inference
Calendar Description of Course:
Nature of Course
Prerequisites (or special instructions):
Add the statement, "Students with credit for MATH 475 may not take STAT 460
for further credit."
What course (courses), if any, is being dropped from the calendar if this course is
approved: ?
MATH 475.
2. Scheduling
How frequently will the course be offered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
0. Objectives of the Course
4. Budgetary and Space Requirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual.
Space
Equipment
S.'Approval
?
Date,
Dean
is
artm.ntairman
SCUS 73-34b,- (When completing this form,
Attach course outline).
SCUS
for instructions see Memorandum SCUS 73-34a.
fl: Change of Label and Title Only :$
?
Appendix E,
SENATE COMMITTEE ON UNDERGRADUATESTUDIES
COURSE PROPOSAL FORM
?
FOR INFORMATION
1.
Calendar Information
?
Department: Mathematics and Statistics
04
Abbreviation Code: STAT Course Number: 480 Credit Hours: 3 Vector: 3-0-0
Title of Course:
?
Probability_Theory
Calendar Descri p
tion of Course:
Nature of Course
Prerequisites
(or
special instructions):
-
STAT 380 (or MATH 387).
Students with credit for MATH 487 may
not
take STAT 480 for further
credit.
What course (courses), if any, is being dro
pp
ed from the calendar if this course is
approved: MATH 487
2.
Schedulina
How frequently will the course be offered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
3.
Objectives of the Course
The chan g
e is part of a major relabelling of probability and statistics courses.
4.
Budoetar
y
and S
p
ace Re
q
uirements (for information only)
What additional resources will be required in the following areas:
Faculty
Staff
Library
Audio Visual
Space
Equipment
5.
Approval
?
"OCT n F N87
Date:
?
------------------------
4
---------------------
Depar trnent Chairman
?
Chairman, SCUS
SCUS 73-34b:- (When completing this frm, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
Appendix
B3
SENATE COMMITTEE ON UNDERGRADUATE STUDIES
COURSE PROPOSAL FORM
?
FOR INFORMATION
o4)
•1.
Calendar Information ?
Department:
Mathematics & Statistics
Abbreviation
Code:_
STAT
Course Number:
490
?
Credit Hours:
3 ?
Vector:
_3-1-0
Title of Course:
?
Selected Topics in Probability and Statistics
Calendar Description of Course:
Topics in areas of probability and statistics not covered in the regular
undergraduate curriculum of the department.
Nature of Course
?
Lecture/Tutorial
Prerequisites (or special instructions):
Dependent on the topic covered.
What course (courses), if any, is being dropped from the calendar if this course is
approved: mr A 449-3.
2. Scheduling
How frequently will
the course be offered?
Semester in which the course will first be offered?
Which of your present faculty would be available to make the proposed offering
possible:
3.
Objectives of the Course
The proposed relabelling of courses in probability and statistics with the
code, 'STAT', would otherwise leave the department with no means of offering
a selected topics course in this field.
4.
Budgetary and Space Requirements (for information only)
What additional resources will be required in the following
areas:
Faculty
Staff
Library
Audio Visual.
Space
Equipment
5.
Approval
Date:
a
Departhet
ChChairman
irman, SCUS
SCUS 73-34bs-
(When completing this form, for instructions see Memorandum SCUS 73-34a.
Attach course outline).
