Applied Statistics (STAT)
COURSE OFFERINGS
STAT 325 Applied Statistics I
3. 000 Credits
Prerequisites: MATH 113 or MATH 115 or MPLS 116
A study of the fundamental concepts and methods of probability
and statistics. Topics include counting problems, discrete
probability, random variables and probability distributions,
special distributions, sampling distributions, the central limit
theorem, introduction to hypothesis testing, and the use of
statistical computer packages for data analysis. Students can
receive credit for only one of MATH 363, STAT 363, SOC 383
and STAT 325. (F, W).
STAT 363 Introduction to Statistics
3. 000 Credits
Frequency distribution and descriptive measures. Populations,
sampling and statistical inference. Elementary probability and
linear regression. Use of statistical computer packages to
analyze data. Students can receive credit for only one of STAT
325, STAT 363, MATH 363, and SOC 383. Students intending
to elect this course should have had at least one year of high
school algebra. (F, W, S).
STAT 390 Topics in Applied Statistics
3. 000 Credits
Must be enrolled in one of the following Levels:
Undergraduate
A course designed to offer selected topics in applied statistics.
The specific topic or topics will be announced together with the
prerequisites when offered. Course may be repeated for credit
when specific topics differ. (OC)
STAT 425 Applied Statistics II
3. 000 Credits
Prerequisites: STAT 325 or STAT 363 or MATH 363 or
SOC 383
A continuation of STAT 325. This course treats both the
principles and applications of statistics. Elementary theory of
estimation and hypothesis testing, the use of the normal, chisquare,
F and t distributions in statistics problems will be
covered. Other topics are selected from regression and
correlation, the design of experiments, analysis of variance,
analysis of categorized data, nonparametric inference, and
sample surveys. (W).
STAT 430 Applied Regression Analysis
3. 000 Credits
Prerequisites: STAT 425
Topics include single variable linear regression, multiple linear
regression and polynomial regression. Model checking
techniques based on analysis of residuals will be emphasized.
Remedies to model inadequacies such as transformations will be
covered. Basic time series analysis and forecasting using
moving averages and autoregressive models with prediction
errors are covered. Statistical packages will be used. Students
cannot receive credit for both STAT 430 and STAT 530.
STAT 440 Design and Analysis of Expermt
3. 000 Credits
Prerequisites: STAT 425
An introduction to the basic methods of designed
experimentation. Fixed and random effects models together with
the analysis of variance techniques will be developed.
Specialized designs including randomized blocks, latin squares,
nested, full and fractional factorials will be studied. A statistical
computer package will be used. (W).