Statistics: STA

Lower-Division Courses

STA X01. Introduction to Data Science.

An introduction to the principles and practice of data science for business applications. Explore tidying, summarizing, and visualizing data; statistical computing in R; linear regression; introduction to predictive modeling and out-of-sample model validation; uncertainty quantification using resampling methods; basic probability models, including the normal and binomial distributions; and statistical hypothesis testing.

STA X01H. Introduction to Data Science: Honors.

An introduction to the principles and practice of data science for business applications. Explore tidying, summarizing, and visualizing data; statistical computing in R; linear regression; introduction to predictive modeling and out-of-sample model validation; uncertainty quantification using resampling methods; basic probability models, including the normal and binomial distributions; and statistical hypothesis testing.

STA X09. Elementary Business Statistics.

Training in the use of data to gain insight into business problems; describing distributions (center, spread, change, and relationships), producing data (experiments and sampling), probability and inference (means, proportions, differences, regression and correlation).

STA X09H. Elementary Business Statistics: Honors.

Training in the use of data to gain insight into business problems; describing distributions (center, spread, change, and relationships), producing data (experiments and sampling), probability and inference (means, proportions, differences, regression and correlation).

STA X19S. Topics in Statistics.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence. Transfer credit is awarded for work in an affiliated studies program.

STA X87. Business Analytics and Decision Modeling.

Introduction to some of the basic concepts in quantitative business analysis that are used to support organizational decision making over various time frames. Explores methods that apply to all areas of an organization, with emphasis on financial decision making.

Upper-Division Courses

STA X29S. Topics in Statistics.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence. Transfer credit is awarded for work in an affiliated studies program.

STA X35. Data Science for Business Applications.

Examine data science for business applications at the intermediate level. Explore building and validating predictive models; advanced regression modeling, including an in-depth treatment of regression; models for binary outcomes; and causal inference.

STA X35H. Data Science for Business Applications: Honors.

Examine data science for business applications at the intermediate level. Explore building and validating predictive models; advanced regression modeling, including an in-depth treatment of regression; models for binary outcomes; and causal inference.

STA X40S. Topics in Statistics.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office or the school's BBA Exchange Programs. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence.

STA X71G. Statistics and Modeling.

Focuses on methods used to model and analyze data. Explores multiple regression models and their application in the functional areas of business, time-series models, decision analysis and the value of information, and simulation-based methods.

STA X71H. Statistics and Modeling: Honors.

Focuses on methods used to model and analyze data. Explores multiple regression models and their application in the functional areas of business, time-series models, decision analysis and the value of information, and simulation-based methods.

STA X72T. Topics in Statistics.

STA X72T.11. Computational Finance.

Introduction to the analysis and implementation of numerical methods used in finance. Explore numerical techniques in derivative pricing and optimal asset allocation, such as Monte Carlo and quasi-Monte Carlo simulation, methods for solving partial differential equations, and dynamic programming.

STA X72T.16. Optimization Method in Finance.

Explore quantitative methods and techniques in optimization and simulation, and their use in financial decision making. Discuss theory and application in portfolio selection, options and other derivative pricing, index tracking, risk measures, volatility estimating. Examine linear, quadratic, nonlinear, and integer programming; dynamic programming; robust optimization; Monte Carlo methods and variance reduction techniques. Emphasis will be placed on problem solving with advanced computational programming languages.

STA X72T.21. Time Series Forecasting.

Examine statistical forecasting methods used in business. Discuss Box-Jenkins models; exponential smoothing models; ARCH/GARCH models for varying volatility in financial returns; seasonal adjustment of time series; tests for nonstationary of time series; and modeling multiple time series.

STA X75. Statistics and Modeling for Finance.

Methods used to model and analyze data, especially as applied to problems related to finance. Explores regression models, time-series models, decision analysis and simulation-based methods.

STA X75H. Statistics and Modeling for Finance: Honors.

Methods used to model and analyze data, especially as applied to problems related to finance. Explores regression models, time-series models, decision analysis and simulation-based methods.

STA X76. Intermediate Statistics.

Analysis of forecasting techniques and theory; macroeconomic models; long-range and short-term forecasting; forecasting for the firm, using case material.

STA X87. Business Analytics and Decision Modeling.

Introduction to some of the basic concepts in quantitative business analysis that are used to support organizational decision making over various time frames. Explores methods that apply to all areas of an organization, with emphasis on financial decision making.

Graduate Courses

STA X80. Topics in Seminar in Business Statistics.

Selected topics in the applications of statistical methods to business problems.

STA X80.1. Correlation and Regression Analysis.

STA X80.10. Mathematical Statistics for Applications.

Applications-oriented treatment of mathematical statistics for graduate students who plan to use statistical methods in their research but do not need a highly mathematical development of the subject. Major focus on regression models and related methods. Extensive use of statistical software for data analysis and modeling. Emphasis on understanding how the mathematics of probability and statistics both enables and limits the data analysis that can be done.

STA X80.11. Analysis of Variance.

STA X80.12. Applied Multivariate Methods.

STA X80.13. Statistical Decision Theory.

Development of the mathematical basis of statistical decision theory from both the Bayesian and the frequentist point of view.

STA X80.14. Risk Analysis and Management.

The quantification and analysis of risk, considered from several perspectives: financial risk measures, strategic risk measures, stochastic dominance rules, chance constrained programming, and safety-first approaches.

STA X80.15. Research on Probabilistic Judgment.

Research training and experience for graduate students and advanced Canfield Business Honors Program undergraduate students who are interested in probabilistic judgment.

STA X80.16. Probability and Science in the Courtroom.

The role of probability and scientific reasoning in legal judgments: differences between probability evidence and other types of evidence; legal and psychological implications of these differences; the role of statistics, formal analyses, and expert opinions in legal decisions; their impact on judges and jurors.

STA X80.17. Predictive Modeling.

Introduction to statistical methods for prediction including regression analysis, logistic and multinominal regression, classification and regression trees, bias-variance trade-off, cross validation, variable selection, principal component regression and partial least squares regression.

STA X80.18. Learning Structures and Time Series.

Introduction to exploring data analysis, clustering, dimension reduction, networks, text timing, and time series.

STA X80.19. Time Series.

STA X80.2. Design of Experiments.

STA X80.3. Statistical Computing with SAS.

STA X80.4. Nonparametric Methods.

STA X80.5. Statistical Consulting.

STA X80.6. Survey Research Methods.

STA X80.7. Forecasting.

Development of forecasting techniques for use in business applications.

STA X80.8. Cybernetics and the Law: Societal, Economic, and Other Problems.

STA X80.9. Applied Linear Models.

Theory and application of linear models in empirically oriented research in business.

STA X80N. Topics in Statistics.

STA X80N.1. Advanced Statistics and Econometrics with R.

STA X81. Sampling.

Theory of sampling; sample design, including stratified, systematic, and multistage sampling; nonsampling errors.

STA X84N. Topics in Business Analytics.

Selected topics in business analytics.

STA X87. Business Analytics and Decision Modeling.

Introduction to some of the basic concepts in quantitative business analysis that are used to support organizational decision making over various time frames. Explores methods that apply to all areas of an organization, with emphasis on financial decision making.

STA X87C. Business Analytics and Decision Modelling for Executives.

Examine risky decision-making with an emphasis on case studies that show how Excel models can be used to improve decision-making.

Professional Courses

STA X87. Business Analytics and Decision Modeling.

Introduction to some of the basic concepts in quantitative business analysis that are used to support organizational decision making over various time frames. Explores methods that apply to all areas of an organization, with emphasis on financial decision making.