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ANALYZE AND FORECAST USING LARGE DATA SETS
Gain confidence in building reliable data analyses to make projections of business intelligence and performance. Utilize the fundamental analytical tool - regression - for discovering, analyzing, and forecasting relationships. Acquire a solid understanding of the methods, using intuitive graphical approaches to explain and motivate regression and forecasting models.
WHAT YOU'LL LEARN
Forecasting Models
- Discover, analyze, and forecast relationships among large data sets (“Big Data”)
- Analyze case studies to gain a thorough consideration of the models applications and gain confidence when using data to make analyses, forecasts, and projections
- Model customer retention rates, develop an optimal bidding strategy in a sealed bid process, hedge your firm’s revenue, or forecast future profitability of individual customers, monthly sales, or daily stock prices by charting a successful course with regression and forecasting methods
- Random samples
- Random walks
- Moving averages
Regression Analytics
- Apply regression to past relationships looking for trends, seasonal patterns, and data correlations that can predict the future reliably
- ARIMA (Autoregressive Integrated Moving Average)
- Regression case studies
- Autoregression
Evaluate and Present Findings
- Develop the acumen to competently evaluate findings and analyses presented by others
- Interact with data executives on the topic of data-driven business intelligence
ATTENDING THIS COURSE
Individuals
Individuals
This course is designed for professionals with limited to moderate knowledge of statistics who want a refresher in the tools and models in practical application.
Teams
Teams
Organizations often send pairs or small teams, to support the launch of new initiatives.
Requirements & Credit
Requirements & Credit
There are no prerequisites for this course. Participants earn 1.4 CEUs and/or 14 CPEs for this course, as well as a certificate of completion. Our classes are available for university credit. Please contact us for more information.
Practical Even for Non-Experts
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.
Instructors
Thomas Sager
Thomas Sager
Professor of Statistics, Information, Risk & Operations Management
Thomas Shively
Thomas Shively
Professor of Statistics, Information, Risk & Operations Management
Demonstrate Your Expertise with a Certificate
REIMBURSEMENT OPTIONS
Learn more about course credits and options for course reimbursement. Get tips on the best way to approach your manager and download a customizable template to facilitate making the ask.
COURSE LOCATION
In person courses take place at the AT&T Executive Education and Conference Center and adjoining Rowling Hall on the UT campus in Austin. These world-class facilities provide a comfortable and convenient learning environment, with direct access to the 40 acres of campus and within walking distance of downtown Austin. Live online and on-demand course options are available for many courses.
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