Searching…

University Catalog

Print Page



STAT 501. Credit By Arrangement

Credits: 1-4 View Details
Description: Credit By Arrangement.
Semester Offered:
  • Fall
  • Spring
  • Summer


STAT 515. Data Mining

Credits: 3 View Details
Description: Data mining principles and applications. Predictive modeling techniques for large data sets include classification and regression trees, logistic regression, neural networks, random forests and boosted trees. Handle missing values and outliers. Compare models and deploy best model to predict new data. Hands-on use of data mining software.
Prerequisites: STAT 321
Semester Offered: Spring


STAT 517. Applied Probability and Simulation

Credits: 3 View Details
Description: Probability distributions and random variables, simulation of random variates, probability modeling, applications to Markov chains, queueing models, reliability and survival; use of software.
Prerequisites: One programming course and MATH 211 or equivalent
Semester Offered: Spring


STAT 518. Advanced SAS Programming

Credits: 3 View Details
Description: Mechanics of Macro Processing, Macro variables, Macro programs, Macro Programming Language elements and techniques, storage and reuse of macros, interfaces to macro facility, SQL procedure. Applications to data query, retrieval, and sundry manipulation.
Prerequisites: STAT 304
Semester Offered: Fall


STAT 521. Applied Regression Methods

Credits: 3 View Details
Description: Advanced regression methods focused on complex real-world data. Model checking and diagnostics, model building, transformations, polynomial regression, logistic regression, general linear models, nonparametric regression methods.
Prerequisites: STAT 321
Semester Offered: Spring


STAT 524. Statistical Design for Process Improvement

Credits: 3 View Details
Description: A study of statistically designed experiments which have proven useful in product development and process improvement; topics include randomization, blocking, factorial treatment structures, fractional factorial designs, screening designs, Taguchi methods, response surface methods; use of statistical software.
Prerequisites: STAT 321
Semester Offered: DEMAND


STAT 527. Applied Time Series

Credits: 3 View Details
Description: A study of the most useful techniques of analysis and forecasting using time series data. Topics include an introduction to forecasting, time series regression, decomposition methods, smoothing, smoothing techniques, basic techniques of Box-Jenkins methodology; use of statistical software.
Prerequisites: STAT 321
Semester Offered: DEMAND


STAT 530. Multivariate Statistical Methods

Credits: 3 View Details
Description: Principal component analysis, factor analysis, discriminant analysis, cluster analysis, manova, profile analysis, repeated measures; applications and use of statistical software.
Prerequisites: STAT 321
Semester Offered: DEMAND


STAT 533. Nonparametric Statistics

Credits: 3 View Details
Description: Efficiency comparison of mean and median, one and two sample location problems, effect of alternative score functions, randomization and permutation tests, the independence problem, and selected problems in regression. Use of statistical software.
Prerequisites: STAT 321
Semester Offered: DEMAND


STAT 536. Applied Categorical Data Analysis

Credits: 3 View Details
Description: Introduction to the analysis of discrete data; log-linear models for two-way and multi-way tables; linear logistics regression models; association models and models of symmetry; applications, use of statistical software.
Prerequisites: STAT 321
Semester Offered: DEMAND


STAT 540. Topics in Statistics

Credits: 3 View Details
Description: Study of modern topics in theoretical or applied statistics.
Semester Offered: Spring


STAT 542. Business Statistics

Credits: View Details
Description: Numerical and graphical descriptive statistics and inferential procedures. Selected statistical topics with major emphasis on applications in business.
Semester Offered: Fall


STAT 547. Basic Elements of Probability Theory

Credits: 3 View Details
Description: A more mathematical treatment of probability distributions than STAT 417. Probability concepts and laws; sample spaces, combinations and permutations, Bayes' theorem, discrete and continuous random variables, expected value, distribution of functions of random variables, two-demensional variates, central limit theorem; T, F, and chi-square distributions;
Prerequisites: MATH 320 or MATH 321
Semester Offered: Fall


STAT 548. Basic Elements of Statistical Theory

Credits: 3 View Details
Description: Theory of estimation and hypothesis testing; maximum likelihood, method of moments, likelihood ratio tests; elementary mathematical functions illustrate theory.
Prerequisites: STAT 447 or STAT 547
Semester Offered: Spring


STAT 588. Type B Workshops

Credits: 1-3 View Details
Description: May be repeated to a max. of 9 credits.
Semester Offered:
  • Fall
  • Spring
  • Summer


STAT 600. Special Problems

Credits: 1-3 View Details
Description: Independent study for advanced students wishing to work out a special problem in the major area of concentration.
Semester Offered:
  • Fall
  • Spring
  • Summer


STAT 615. Data Mining for Analytics

Credits: 3 View Details
Description: Data mining principles and applications. Predictive modeling techniques for large data sets include classification and regression trees, logistic regression, neural networks, random forests and boosted trees. Handle missing values and outliers. Compare models and deploy best model to predict new data. Extensive hands-on use of data mining software.
Prerequisites: STAT 242 or equivalent
Semester Offered: Spring


STAT 617. Statistical Theory

Credits: 3 View Details
Description: Probability and univariate distributions, binomial, Poisson, gamma, normal distributions, multivariate distributions, distributions of functions of random variables, limiting distributions, significance tests, estimation.
Semester Offered: Fall


STAT 618. Survival Analysis

Credits: 3 View Details
Description: Estimation of survival probabilities, families of two-sample rank tests, distribution functions for failure times, Cox regression model, proportional hazards model, graphical and other methods for assessing model adequacy, Poisson regression models, competing risks, meta-analysis.
Prerequisites: STAT 321
Semester Offered: Spring


STAT 619. Generalized Linear Models

Credits: 3 View Details
Description: Likelihood theory, exponential families, model specification, model checking and diagnostics, logistic and ordinal regression, log linear models, gamma regression models, generalized estimating equations, and generalized linear mixed models.
Prerequisites: STAT 321
Semester Offered: Fall


STAT 620. Bayesian Data Analysis

Credits: 3 View Details
Description: Prior distributions, Bayesian statistical models, parameter estimation, Markov Chain Monte Carlo, hierarchical models, model checking, hierarchical regression.
Prerequisites: STAT 548, STAT 617
Semester Offered: DEMAND


STAT 621. Design and Analysis of Experiments

Credits: 3 View Details
Description: Review of fundamentals of Experimental Design. Randomized complete and incomplete block designs. Latin squares and rectangles, Graeco-Latin Squares designs. Designs for cross-over trials. Cyclic, alpha and Lattice Designs. Incomplete block designs with factorial treatments. Confounding. Franctional replication in factorial designs.
Prerequisites: STAT 521
Semester Offered: DEMAND


STAT 649. Statistical Consulting

Credits: 2 View Details
Description: Provide statistical consulting for clients from other departments. Assist client in design of experiment, summarization of data, data analysis and interpretation of results.
Prerequisites: STAT 518, STAT 521
Semester Offered:
  • Fall
  • Spring


STAT 650. Statistics Seminar

Credits: 1 View Details
Description: Student presentations of current research in applied statistics.
Semester Offered: Spring


STAT 660. Data Visualization for Analytics

Credits: 3 View Details
Description: Explore visual representations of data for exploratory analysis. Traditional and contemporary visual techniques to improve the understanding and communication of complex data. Good design practices for visualization and presentation of analytics. Extensive use of software.
Prerequisites: One of: STAT 219, STAT 239, STAT 242, STAT 353.
Semester Offered: Spring






The contents in this catalog and other university publications, policies, fees, bulletins or announcements are subject to change without notice and do not constitute an irrevocable contract between any student and St. Cloud State University.