Chris Anderson is a professor at the Cornell School of Hotel Administration. Prior to his appointment in 2006, he was on the faculty at the Ivey School of Business in London, Ontario, Canada. Professor Anderson’s main research focus is on revenue management and service pricing. He actively works in the application and development of revenue management across numerous industry types, including hotels, airlines, and rental car and tour companies, as well as numerous consumer packaged goods and financial services firms. Professor Anderson’s research has been funded by numerous governmental agencies and industrial partners. He serves on the editorial board of the Journal of Revenue and Pricing Management and is the regional editor for the International Journal of Revenue Management. At the School of Hotel Administration, Professor Anderson teaches courses in revenue management and service operations management.
Implementing Scientific Decision Making
Decision Making
Implementing Scientific Decision Making ()
Cornell Course
GET STARTED NOWCOURSE OVERVIEW
Summary statistics are one way to forecast uncertain outcomes, and the statistical results can be used to make decisions or guide strategy. Since summary statistics are based on a data sample, they typically inform intuitive decision-making. That is, the model requires interpretation which relies on the business intuition of the person using it.
You'll learn how to examine sample data scientifically to limit any generalizations to only the patterns that have the strongest statistical support. As always, intuition and business knowledge play an important role in the process, but this course will prepare you to apply a level of scientific rigor that will lead to better results.
KEY COURSE TAKEAWAYS
- Formulate a question as a null and alternate hypothesis
- Calculate a test statistic from sample data
- Identify the statistical test most appropriate for testing your hypothesis
- Determine the likelihood of finding a result at least as extreme as the test statistic assuming the null hypothesis
How It Works
Course Length
2 weeks
Effort
3-5 hours per week
Format
100% online, instructor-led
Course Author
Who Should Enroll
- Analysts
- Functional Managers
- Executives
- Consultants
- Any professional that uses data to make business decisions
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100% ONLINE
100% ONLINE
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