Courses Offered
Applied Statistics – Spring 2013
STAT 2000. Using Statistics (3). Fall, Spring. Descriptive statistics, probability distributions, estimation, hypothesis testing, regression, contingency tables. Interpretation and misinterpretation of statistical techniques. Does not count toward BSBA degree.
STAT 2110. Elementary Statistical Methods I (3). Fall, Spring. Elementary probability, random variables, probability distributions, sampling, descriptive statistics, sampling distributions, estimation. Prerequisite: credit for MATH 1260 or MATH 1310, or C or better in MATH 1340. Credit not given for both STAT 2110 and MATH 2470.
STAT 2120. Elementary Statistical Methods II (3). Fall, Spring. Estimation, hypothesis testing, regression, correlation, analysis of variance and contingency tables. Prerequisite: C or better in STAT 2110 or equivalent.
STAT 2200. Elementary Business Statistics (5). Elementary probability, random variables, probability distributions, sampling, descriptive statistics, sampling distributions, estimation, hypothesis testing, regression, correlation, analysis of variance and contingency tables. Four hours of lectures and one two-hour laboratory. Prerequisite: C or better in MATH 1260 or MATH 1310, or both MATH 1340 and MATH 1350. Credit not given for both STAT 2200 and MATH 2470, or both STAT 2200 and STAT 2110, or both STAT 2200 and STAT 2120.
STAT 4020. Regression Analysis (3). Fall. Linear, nonlinear and multiple regression and correlation analysis. Prerequisite: Prior credit in STAT 2120 or MATH 4410 is required for enrollment. Students in pre-BSBA, BSBA conditional, or NOADMIT plans are not eligible to enroll..
STAT 4060. Sample Design (3). Spring. Sampling as a tool of scientific inference in research and management. Planning surveys; sample size, stratified, systematic and cluster sampling; sources of error in surveys. Prerequisite: MATH 4410 or consent of instructor.
STAT 4080. Experimental Design (3). Spring. Constructing statistical designs and analyzing resulting data; basic experimental design and analysis of variance. Prerequisite: MATH 4410 or consent of instructor.
STAT 4120. Applied Nonparametric Statistics (3). Nonparametric approach to testing hypotheses; contingency tables, goodness of fit, procedures based on ranks. Prerequisite: MATH 4410 or consent of instructor.
STAT 4140. Statistical Quality Control (3). Statistical process control; Shewhart control charts (variables and attributes); acceptance sampling (single, double and sequential); Dodge-Romig tables. Prerequisite: MATH 4410 and STAT 2120 or STAT 2200, or consent of instructor.
STAT 4160. Time Series Analysis (3). Stochastic stationary and nonstationary models; use in forecasting seasonal and nonseasonal discrete time series; fitting models to time series data. Prerequisite: MATH 4410 or consent of instructor.
STAT 4440. Data Mining in Business Analytics (3). Fall, Spring. Data mining is the analysis of large data sets for the purpose of discovering useful information. This course will cover a variety of data mining applications and algorithms. Topics include regression trees, classification trees, clustering, discriminant analysis, neural networks, link analysis and market basket analysis. Students will be exposed to applications in busines (finance, insurance, manufacturing, marketing), crime detection (identifying criminal patterns, fraud detection), and science (analysis of scientific data). Prerequisite: STAT 2120 and OR 3800 or permission of instructor.
STAT 4910. Studies in Statistics (1-3). On demand. Investigation of selected areas or contemporary problems. May be offered individually and in classes depending on student needs and nature of material. May be repeated.
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