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STAT 271 STATISTICAL ANALYSIS
Credits: 3(3,0,0) Prerequisite: STAT 101
Advanced statistical techniques. Topics include: multiple regression, the analysis of variance,
the analysis of covariance, stepwise approach to multiple regression, nonparametric methods,
time series analysis, use of index numbers in economic data, classical inference and properties
of good estimator (unbiasedness, consistency, efficiency). Students do projects that require use
of statistical packages (SAS, SPSS, etc...) throughout the course.

STAT 272 APPLIED STATISTICS FOR ENGINEERS
Credits: 3 (3,0,0) Prerequisite: STAT 101
The course is designed for engineering problem solving and for creation of statistical thinking
applied to industrial processes. The course covers: principles of engineering data collection;
principles of experimentation; confidence intervals and significance tests; one-, two-, and multi-
sample studies; regression analysis; assessing, monitoring and improving processes using
statistical methods; process monitoring, control charts, capability analysis, and reliability.
Students employ statistical software (e.g. SAS and SPSS) to perform statistical data analysis and
experiments and work on team projects involving engineering experimentation and data
analysis.