Data Analytics

Business Analytics

Use regression methods and statistical tools to better discover, analyze and forecast relationships among large data sets ("Big Data") to gain confidence in building reliable data analyses to make projections of business intelligence and performance.

Overview Benefits Topics Additional Information Faculty Sessions


The fundamental analytical tool for discovering, analyzing and forecasting relationships is regression. Forecasting applies regression to past relationships, looking for trends, seasonal patterns and hidden correlations that can be predicted reliably into the future. Whether it is modeling customer retention rates, developing an optimal bidding strategy in a sealed bid process, hedging a firm’s revenue, or forecasting future profitability of individual customers, monthly sales, or daily stock prices, managers can chart a successful course with regression and forecasting methods.

All of these and other case studies are covered in this class. In addition, the class conveys a solid fundamental understanding of the methods, using intuitive graphical approaches to explain and motivate regression and forecasting models.

Business Analytics

Explore the ins and outs of data analytics to gain perspective and experience with the complexities of “Big Data” in the business and organizational context.

Two-day Concentrated Program

Registration begins at 8:00 a.m. and class runs 8:30 – 4:30 both days with a one-hour networking lunch included.

Austin, Texas

Enjoy proximity to the vibrancy of the campus and downtown Austin, and the innovative, business-friendly environment of the city.


  • Understand how regression can be used to uncover trends, patterns and data correlations
  • Gain confidence when using data to make analyses, forecasts and projections
  • Develop the acumen to competently evaluate the findings and analyses presented by others
  • Interact with data executives on the topic of data-driven business intelligence


  • Forecasting models
  • Random samples
  • Random walks
  • Autoregression
  • Moving averages
  • ARIMA (Autoregressive Integrated Moving Average)
  • Regression analytics
  • Regression case studies

Additional Information

Prerequisites: None
CEUs: Participants earn 1.4 CEUs and/or 14 CPEs for this course. A certificate of completion will be presented from Texas Executive Education.
Course Credits: 1.00


Thomas Sager

Tom Sager was raised and educated in Iowa. He served in the Army as a trumpet player during the Vietnam War.

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Tom Shively

Dr. Tom Shively is a Professor of Statistics and the Joe B. Cook Professor of Business in the McCombs School of Business at The University of Texas at Austin.

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"Both professors were clear, knowledgeable and kept things practical and basic enough for those of us who aren't experts. Case studies were very helpful."

-Zach Ainsley

St. Jude Medical, Inc.

Course Details

Price: $2,950.00

Data Analytics


11/16/15 - 11/17/15


AT&T Executive Education & Conference Center 1900 University Avenue Austin, TX 78705

Tom Shively
Thomas Sager

05/09/16 - 05/10/16


AT&T Executive Education & Conference Center 1900 University Avenue Austin, TX 78705

Tom Shively
Thomas Sager