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Course Criteria
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3.00 Credits
Principle topics include collecting and summarizing data, probability distributions, analysis of categorical data, introduction to multiple linear regression, experimental design, analysis of variance, and non-parametric methods. Statistical computer software is used. Not open to students who have received credit for MATH 4020. Preq: MATH 3020 with a C or better or STAT 2300 with a C or better.
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3.00 Credits
Introduction to statistical computing packages. Topics include data importation, basic descriptive statistic computation, basic graphic preparation, and statistical analysis methods and procedures. Preq: IE 3610 or MATH 3020 or MGT 3100 or STAT 2300.
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3.00 Credits
Experimental design techniques for use in process development, application of screening experiments and response surface experiments, techniques for process control with implications for product quality control. Includes discussions of the use of statistical computer analyses and interpretations including computer-generated graphics. Preq: MATH 2060.
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3.00 Credits
Introduction to statistical computing packages. Topics include data importation, basic descriptive statistic computation, basic graphic preparation, and statistical analysis methods and procedures. Students are expected to have completed an introductory statistics course before enrolling in this course.
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3.00 Credits
Experimental design techniques for use in process development, application of screening experiments and response surface experiments, techniques for process control with implications for product quality control. Includes discussions of the use of statistical computer analyses and interpretations including computer-generated graphics. Students are expected to have completed a course in multivariable calculus before enrolling in this course.
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3.00 Credits
Role and application of statistics in research; estimation, test of significance, analysis of variance, multiple comparison techniques, basic designs, mean square expectations, variance components analysis, simple and multiple linear regression, and correlation, and nonparametric procedures.
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3.00 Credits
Extended coverage of several methods introduced in STAT 8010: multiple regression model building and diagnostics, experiment design and analysis, and nonparametric methods; mixed models and repeated measures analyses; categorical data analysis; multivariate methods and sampling designs; appropriate use of statistical software. Preq: STAT 8010.
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3.00 Credits
Regression analysis: simple and multiple linear, curvilinear and multiple curvilinear; curve fitting; least squares and computer techniques for fitting of constants and analysis of planned experiments. Offered spring semester only. Preq: STAT 8010.
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3.00 Credits
Principles of scientific sampling; finite population sampling; simple random, stratified, multistage and systematic sampling; optimum allocation; methods of obtaining, processing and reporting survey information; sampling as related to the environment, natural resources and social and economic problems. Preq: STAT 8010.
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3.00 Credits
Basic designs and analysis; data transformations; single degree of freedom, orthogonality and responses in ANOVA; covariance; response surfaces; incomplete blocks; introduction to least squares analysis of experiments; uses of standard computer programs for selected analyses. Preq: STAT 8010.
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