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Course Criteria
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3.00 Credits
Credits: 3 Introduction to modern exploratory data analysis techniques. Topics include graphical techniques, such as box plots, parallel coordinate plots, and other graphical devices, re-expression and transformation of data, order statistics, influence and leverage, and dimensionality reduction methods such as projection pursuit. Prerequisites STAT 350 or 354, or equivalent. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered IR
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3.00 Credits
Credits: 3 Introduction to design and analysis of sample surveys. Sample designs include simple random sampling; systematic sampling; and stratified, cluster, and multistage sampling. Analytical methods include sample size determination, ratio and regression estimation, imputation for missing data, and nonsampling error adjustment. Practical problems encountered in conducting a survey are discussed. Methods applied to case studies of actual surveys. Class project may be required. Prerequisites STAT 350 or 354 and STAT 362 or permission of instructor. Notes Recommended for students of decision, information, social sciences, and mathematics. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered F
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1.00 - 3.00 Credits
Credits: 1-3 Directed self-study of special topics of current interest in statistics. Prerequisites 60 undergraduate credits; must be arranged with instructor and approved by the department chair before registering. Notes May be repeated for maximum 6 credits if topics are substantially different. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Topics of special interest to undergraduates. Prerequisites 60 undergraduate credits and permission of instructor; specific prerequisites vary with nature of topic. Notes May be repeated for maximum 6 credits if topics substantially differ. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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1.00 Credits
Credits: 1 Introduction to the SAS Data Step and Base SAS Procedures. Preparation for graduate students in use of SAS for other graduate courses offered by department. Topics include observation and variable structures, data interfaces, formats, functions, and procedures for summarizing and displaying data. Prerequisites Course in statistics and experience with Microsoft OS. Notes At most one of STAT 501-503 can be applied to certificate programs in statistics. Hours of Lecture or Seminar per week 1 Hours of Lab or Studio per week 0 When Offered S
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1.00 Credits
Credits: 1 Introduction to SAS/GRAPH. Continued preparation beyond STAT 501 for graduate students in the use of SAS for other graduate courses offered by department. Topics include SAS/GRAPH and SAS/GRAPH procedures, SAS/GRAPH output options and in-depth coverage of the GOPTIONS, GDEVICE, GCHART, GPLOT, and GSLIDE procedures. Prerequisites Working knowledge of SAS. Notes At most one of STAT 501-503 can be applied to certificate programs in statistics. Hours of Lecture or Seminar per week 1 Hours of Lab or Studio per week 0 When Offered S
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1.00 Credits
Credits: 1 Introduction to SAS Macro Language. Continued preparation beyond STAT 501 for graduate students in use of SAS for other graduate courses offered by department. Topics include macro language processing, macro variables, defining and calling macro variables, macro quoting, macro facility error messages, and examples of efficient code using macros. Prerequisites Working knowledge of SAS. Notes At most one of STAT 501-503 can be applied to certificate programs in statistics. Hours of Lecture or Seminar per week 1 Hours of Lab or Studio per week 0 When Offered S
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3.00 Credits
Credits: 3 Statistical methods for analysis of experimental data, including ANOVA and regression. Parametric and nonparametric inference methods appropriate for a variety of experimental designs are presented along with data analysis using SPSS. Intended primarily for researchers in the natural, social, and life sciences. Prerequisites STAT 250 or equivalent. Notes Can be used to satisfy requirements for certificates in federal statistics and biostatistics, but not MS in statistical science. Certificate program students granted credit for only one of STAT 535 or 554. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered F
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3.00 Credits
Credits: 3 Course in probability with applications in computer science, engineering, operations research, and statistics. Random variables and expectation, multivariate and conditional distributions, conditional expectation, order statistics, transformations, moment generating functions, special distributions, limit theorems. Prerequisites MATH 213 and STAT 346, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered F, S
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3.00 Credits
Credits: 3 Application of basic statistical techniques. Focus is on the problem (data analysis) rather than on the theory. Topics include one- and two-sample tests and confidence intervals for means and medians, descriptive statistics, goodness-of-fit tests, one- and two-way ANOVA, simultaneous inference, testing variances, regression analysis, and categorical data analysis. Normal theory is introduced first with discussion of what happens when assumptions break down. Alternative robust and nonparametric techniques are presented. Prerequisites STAT 346 or permission of instructor. Notes Certificate program students granted credit for only one of STAT 535 or 554. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered F, S
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