Chris Anderson is a professor at the Cornell School of Hotel Administration. Prior to his appointment in 2006, he was on faculty at the Ivey School of Business in London, Ontario, Canada. His main research focus is on revenue management (RM) and service pricing. He actively works with industry, across numerous industry types, in the application and development of RM, having worked with a variety of hotels, airlines, rental car and tour companies, as well as numerous consumer packaged goods and financial services firms. 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, he teaches courses in revenue management and service operations management.
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.
- 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
Who Should Enroll
- Functional Managers
- Any professional that uses data to make business decisions