103. Fundamentals of Statistics.
Prerequisite: Math Placement Test or MATH 100
(with a grade of "C" or better).
An introduction to statistical reasoning. Students
learn how statistics has helped to solve major problems in economics, education,
genetics, medicine, physics, political science, and psychology. Topics
include: design of experiments, descriptive statistics, mean and standard
deviation, the normal distribution, the binomial distribution, correlation
and regression, sampling, estimation, and testing of hypothesis.
203. Statistics.
Prerequisite: Math 162 or 132 (with grade of "C"
or better).
An introduction to statistical methodology and
theory using the techniques of one-variable calculus. Topics include: experimental
design, descriptive statistics, probability theory, sampling theory, inferential
statistics, estimation theory, testing hypotheses, correlation theory,
and regression. (Note: Students may not receive credit for both STAT
203 & 335.)
303. SAS Programming and Applied Statistics.
Prerequisite: STAT 103 or 203 or 335.
An introduction to SAS programming in the context
of practical problems taken from applied statistics. SAS programming includes
extensive data-set manipulations such as inputting, from raw data and external
files, subsetting, working with single and multidimensional arrays, SAS
functions, basic macros. SAS procedures include MEANS, FREQ, GLM, PLOT,
REG, UNIVARIATE, and selected topics from IML, LOGISTIC, MIXED, NLIN. Statistical
topics include t-tests, simple and multiple regression, ANOVA, categorial
analysis, repeated measures.
304. Probability & Statistics I. (MATH
304)
Prerequisites: MATH 263; STAT 203 or 335.
A calculus-based introduction to probability theory.
Combinatorial analysis, random walks, conditional probability and stochastic
independence, the binomial, Poisson and exponential distributions, the
normal approximation to the binomial distribution, random variables, expectation,
laws of large numbers, moment generating functions and Markov chains
305. Probability & Statistics II. (MATH
305)
Prerequisite: STAT 304.
A continuation of STAT 304. Hypothesis testing,
limit theorems, point and interval estimation, linear correlation, and
linear regression.
306. Stochastic Processes. (MATH 306)
Prerequisites: STAT 203 or 335; MATH 212.
Finite-state Markov processes. Markov chains,
classification of states, long-run behavior, continuous time processes
such as the Poisson process, birth and death processes, random walks, and
Brownian motion. Examples in genetics, population growth, inventory, cash
management, and the gambling theory.
307. Statistical Design and Analysis of Experiments.
Prerequisites: STAT 203 or 335.
Comparative experiments, analysis of variance,
fixed and random effects models, randomized block designs, Latin square
designs, incomplete block designs, and factorial designs. Use of packaged
computer programs such as SPSS or SAS.
308. Applied Regression Analysis.
Prerequisites: STAT 203 or 335.
Simple and multiple linear regression methods
including weighted least squares and polynomial regression. Multiple comparison
estimation procedures, residual analysis, and other methods for studying
the aptness of a proposed regression model. Use of packaged computer programs
such as SPSS and SAS.
335. Introduction to Biostatistics. (BIOL
335) (4)
Prerequisites: MATH 162 or 132; BIOL 102.
An introduction to statistical methods used in
designing biological experiments and in data analysis. Topics include probability
and sampling distribution, design of biological experiments and analysis
of variance, regression and correlation, stochastic processes, and frequency
distributions. Computer laboratory assignments with biological data. (Note:
Students may not receive credit for both STAT 203 & 335.)
356. Computer Principles of Modeling and Simulation.
(COMP 356)
Prerequisites: COMP 170 or 125; STAT 203 or 335.
Random number generators, random variable generators,
principles of modeling, Monte Carlo methods, and introduction to simulation
languages such as GPSS, SIMSCRIPT, or SLAM. Applications to management
sciences and decision-making.
358. Methods in Operations Research. (MATH
358)
388. Special Topics in Statistics. (1-3)
Prerequisite: STAT 303.
Advanced topics in statistics, such as multivariate
analysis, sampling theory, non-parametric methods, decision theory, and
Bayesian analysis.
Course title and content vary; prerequisites are
established by the instructor. May be repeated for credit.
391. Internship in Actuarial Science. (1-3)
Prerequisites: STAT 304, 396, and approval of
the internship director; open only to junior/senior majors.
An opportunity to obtain experience in actuarial
science in a professional environment. Placement requires approval of the
internship coordinator and acceptance by an employer. Students will submit
written reports based upon their internship activities. The number and
frequency of reports must be approved by the internship coordinator. May
be repeated for credit.
396. Actuarial Seminar I. (1)
Prerequisites: MATH 212, 263.
Topics in calculus of one and several variables
and linear algebra directed toward preparing students for the first actuarial
examination. May be repeated for credit.
397. Actuarial Seminar II. (1)
Prerequisite: STAT 304.
Topics in probability and risk management directed
toward preparing students for the first actuarial examination. May be repeated
for credit.
398. Independent Study. (1-3)
Prerequisite: permission of chair.
Independent study of selected topics in statistics
under the supervision of a faculty member. May be repeated for credit.
399H. Honors Tutorial. (1-3)
Prerequisite: permission of chair.
Independent study of selected topics in statistics
for students in the honors program. May be repeated for credit.
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