# Course List

## Undergraduate Courses

**EXST 2000 Introduction to Microcomputers (3) F,S,Su** *2 hrs. lecture; 2 hrs. lab. Credit will not for given for this course and CSC 1100,
ISDS 1100, and LIS 2001*. A user-oriented introduction to microcomputers and applications software; terminology;
hardware; software: the operating system, word processing, spreadsheets, data management,
graphics, communications.

**EXST 2201 Introduction to Statistical Analysis (4) F,S** *3 hrs. lecture; 2 hrs. lab. Prereq.: MATH 1021 or equivalent*. Descriptive statistics; inferential statistical methods including confidence interval
estimation and hypothesis testing for one and two population means and proportions;
one-way analysis of variance; simple linear regression and correlation; analysis of
categorical data. *[*General Education Course]*

**EXST 3201 Statistical Analysis II (4) S** *Prereq.: EXST 2201 or equivalent. 3 hrs. lecture; 2 hrs. lab*. Applied statistical modeling: multiple regression, variable selection, serial correlation,
repeated measures, multivariate tools, logistic regression, blocking and factorial
design, categorical data analysis, and nonparametric techniques.

**EXST 3999 Supervised Independent Study and Research (1-4) V** *Prereq.: consent of instructor. May be taken for a max. of 8 sem. hrs. of credit with
consent of department head*. Investigation of areas of interest not covered in other departmental courses, under
the guidance of departmental faculty.

## Senior/Graduate Courses

**EXST 4012 Introduction to Sampling Techniques (3) Su** *Prereq.: EXST 2201 or equivalent*. Simple random, stratified random, cluster, systematic, multistage, multiphase, and
unequal probability sampling procedures methods and applications; ratio and regression
estimation; non-response and non-sampling errors.

**EXST 4025 SAS Programming (3) Su** *Prereq.: EXST 2201 or equivalent*. Reading, processing, manipulating, transforming, and outputting data in various
formats; descriptive and summary statistics procedures; subsetting and combining data
sets; DO loops and arrays; industry standard programming practices.

**EXST 4050 Principles and Theory of Statistics (4) F** *Prereq.: EXST 2201 or equivalent and MATH 1550 or equivalent. 3 hrs. lecture; 2 hrs.
lab*. Probability distributions as models for real-world processes; sampling distributions
and the central limit theorem; estimation and confidence region methods; principles
of hypothesis testing; modeling; emphasis on links between theory, methodology, and
application.

**EXST 4087 Special Topics in Applied Statistics (3) V** *Prereq.: EXST 2201 or equivalent. May be taken for a max. of 6 sem. hrs. of credit
when topics vary*.

## Graduate Courses

**EXST 7003 Statistical Inference I (4) F,S** *3 hrs. lecture; 2 hrs. lab. Prereq.: MATH 1021 or equivalent. Credit will be given
for only one of the following: EXST 7003, 7004, 7005, 7009*. Basic concepts of statistical models and sampling; descriptive and inferential methods;
normal, t, chi-square, and F distributions; tests of hypothesis and estimation, analysis
of variance, correlation, regression, analysis of categorical data; emphasis on social
and behavioral sciences research problems; computer software applications.

**EXST 7004 Experimental Statistics I (4) F,S** *3 hrs. lecture; 2 hrs. lab. Prereq.: MATH 1021 or equivalent. Credit will be given
for only one of the following: EXST 7003, 7004, 7005, 7009*. Basic concepts of statistical models and use of samples; measures of variation and
central tendency; normal, t, chi-square, and F distributions; test of hypothesis,
analysis of variance, regression, and correlation; emphasis on laboratory-oriented
sciences research problems; computer software applications.

**EXST 7005 Statistical Techniques I (4) F,S** *3 hrs. lecture; 2 hrs. lab. Prereq.: MATH 1021 or equivalent. Credit will be given
for only one of the following: EXST 7003, 7004, 7005, 7009*. Basic concepts of statistical models and sampling methods, descriptive statistical
measures, distributions, tests of significance, analysis of variance, regression,
correlation, and chi-square; emphasis on field-oriented life sciences research problems;
computer software applications.

**EXST 7009 Statistical Methods I—Web-Based (3) V** *Prereq.: MATH 1021 or equivalent and knowledge of SAS statistical analysis software.
Credit will be given for only one of the following: EXST 7003, 7004, 7005, 7009*. Basic concepts of statistical models and use of samples; measures of variation and
central tendency, normal, t, chisquare, and F distributions; tests of hypothesis;
analysis of variance, regression, and correlation; emphasis on field oriented life
science research problems.

**EXST 7011 Nonparametric Statistics (3) Su** *Prereq.: EXST 7003 or 7004 or 7005 or equivalent*. Nonparametric one and two-sample location and distribution tests, including binomial,
chi-square, Kolmogorov-Smirnov, Mann-Whitney U, Wilcoxon; analyses of variance, including
Cochran's Q, Kruskal-Wallis, Friedman; correlation and regression, including Kendall's
tau, Spearman's rho, and point biserial.

**EXST 7012 Fundamental Sampling Techniques (3) S** *Prereq.: EXST 7003 or 7004 or 7005 or equivalent*. Simple and stratified random sampling; ratio and regression estimation; cluster,
multistage and multiphase sampling procedures; systematic sampling; nonresponse and
nonsampling errors; links between methodology and application emphasized.

**EXST 7013 Statistical Inference II (4) S** *Prereq.: EXST 7003 or equivalent. 3 hrs. lecture; 2 hrs. lab. Credit will be given
for only one of the following: EXST 7013, 7014, 7015, 7019*. Analyses of variance and experimental designs; completely randomized and complete
block designs; latin square designs; split plot; arrangements of treatments; multiple
comparisons; covariance analysis; multiple and curvilinear regression techniques;
emphasis on social and behavioral sciences research problems.

**EXST 7014 Experimental Statistics II (4) F** *Prereq.: EXST 7004 or equivalent. 3 hrs. lecture; 2 hrs. lab. Credit will be given
for only one of the following: EXST 7013, 7014, 7015, 7019*. Multiple classification analysis of variance and covariance, individual degrees
of freedom, factorial arrangement of treatments, and multiple regression; emphasis
on science/laboratory research problems.

**EXST 7015 Statistical Techniques II (4) F,S** *Prereq.: EXST 7005 or equivalent. 3 hrs. lecture; 2 hrs. lab. Credit will be given
for only one of the following: EXST 7013, 7014, 7015, 7019*. Multiple classification analyses of variance and covariance, sampling designs, parameter
estimation, multiple regression and correlation, tests of specific hypothesis, and
factorial experiments; emphasis on field-oriented life sciences research problems.

**EXST 7019 Statistical Methods II—Web-Based (3) V** *Prereq.: EXST 7003 or 7004 or 7005 or 7009 or equivalent and knowledge of SAS statistical
analysis software. Credit will be given for only one of the following: EXST 7013,
7014, 7015, 7019*. Multiple classification analyses of variance and covariance; sampling designs, parameter
estimation, multiple regression and correlation, tests of specific hypotheses, and
factorial experiments; emphasis on field-oriented life science research problems.

**EXST 7025 Biological Population Statistics II (3) V** Prereq.: *EXST 7015 or equivalent*. Extensive development and application of statistical techniques to parameter estimation
in population dynamics; principles of model building and role of model building in
population management.

**EXST 7031 Experimental Design (3) S** Prereq.: *EXST 7013 or 7014 or 7015 or equivalent*. Comparison of designs, models, and analyses; emphasis on factorial experiments,
complete and incomplete block designs, and confounding.

**EXST 7034 Regression Analysis (3) F** Prereq.: *EXST 7013 or 7014 or 7015 or equivalent; and knowledge of matrix algebra*. Fundamentals of regression analysis, stressing an understanding of underlying principles;
response surfaces, variable selection techniques, and nonlinear regression.

**EXST 7036 Categorical Data Analysis (3) S** *Prereq.: EXST 7013 or 7014 or 7015 or equivalent*. Statistical techniques used in analyzing data from discrete distributions; contingency
tables, loglinear and logit models, logistic regression, and repeated measures for
nominal and ordinal data; emphasis on computer analysis and interpretation.

**EXST 7037 Multivariate Statistics (3) F** *Prereq.: EXST 7013 or 7014 or 7015 or equivalent; and knowledge of matrix algebra*. Comparison of multivariate techniques and analyses; emphasis on discriminant analysis,
factor analysis and principal component analysis, canonical correlation, cluster analysis,
and multivariate analysis of variance.

**EXST 7039 Statistical Methods for Reliability and Survival Data (3) S ***Prereq.: EXST 7013 or 7014 or 7015*. Characteristics of lifetime data; non-parametric methods including Kaplan Meier
estimation; lifetime parametric models, parametric methods for single distribution
data; planning life test; system reliability concepts; failure time regression; accelerated
testing.

**EXST 7060 Probability and Statistics (3) F** *Prereq.: MATH 2057 or equivalent*. Probability, random variables, discrete and continuous distribution functions; expected
values, moment generating functions; functions of random variables.

**EXST 7061 Statistical Theory (3) S** *Prereq.: EXST 7060 or equivalent*. Point estimation; hypothesis testing; interval estimation; large sample theory;
new developments in statistical inference.

**EXST 7083 Practicum in Statistical Consulting I (2) V** *Prereq.: EXST 7013 or 7014 or 7015, and permission of instructor. 4 hrs. independent
study. Pass-fail grading*. Supervised application of statistical techniques to research problems; readings,
oral presentations, and discussions on statistical consulting; problem-solving; mock-consulting
sessions; participation in real-life statistical consulting sessions under faculty
supervision.

**EXST 7084 Practicum in Statistical Consulting II (2) F,S,Su** *Prereq.: EXST 7083 and permission of instructor. 4 hrs. independent study. Pass-fail
grading. May be taken for a max. of 6 sem. hrs. credit*. Primary responsibility for statistical consulting projects under the supervision
of graduate faculty.

**EXST 7085 Special Problem in Statistics (1-3) F,S,Su** *Prereq.: permission of department. Pass-fail grading*. *A technical paper on an advanced topic in statistics is required.* Development of a topic in advanced statistics under faculty supervision.

**EXST 7086 Advanced Seminar in Statistics (1) F,S,Su ***Prereq.: consent of instructor. May be repeated for credit when topics vary. Pass-fail
grading*. Develop and present a 50-minute seminar on an advanced topic in statistics as a
part of the department’s seminar series.

**EXST 7087 Advanced Topics in Statistics (1-3) V** *Prereq.: consent of instructor. May be repeated for credit when topics vary*. Lectures on advanced topics in statistics not covered in other experimental statistics
courses.

**EXST 7142 Statistical Data Mining (3) F** *Prereq.: EXST 7013, 7014, 7015, 7019, or equivalent*. Data preparation tools; model prediction; objects grouping; and variables classification.

**EXST 7151 Bayesian Data Analysis (3)** *Prereq.: EXST 7013 or EXST 7014 or EXST 7015 and EXST 7060 or consent of department
head*. Introduction to Bayesian statistical methods and their application in fields such
as agriculture, biology, engineering and medicine; topics include non-informative,
conjugate and elicited priors; posterior development; common single and multiple parameter
models such as binomial, normal, Poisson, and exponential; hierarchical models; hypothesis
testing and credible sets; posterior simulation via Markov Chain Monte Carlo; and
performance of Bayesian procedures.

**EXST 7152 Advanced Topics in Statistical Modeling (3)** *Prereq.: EXST 7013 or 7014 or 7015 and EXST 7034 or equivalent or consent of department
head*. Regularized linear regression and classification methods; penalized spline fitting
to normal and non-normal data; tree-based methods; ensemble methods including boosting;
support vector machine and kernel-based methods.

**EXST 7999 Independent Study (1-3) F,S,Su** Prereq.: *Permission of instructor. May be taken for a max. of 9 sem. hrs. of credit when topics
vary*. Independent study under the guidance of graduate faculty.

**EXST 8000 Thesis Research (1-12 per sem.)** *"S"/"U" grading*.