Welcome to Experimentation in Data Science. I’m Catherine Truxillo. Since 2000, I’ve been in the Advanced Analytics Education group at SAS, where I’ve taught many courses covering statistics and machine learning topics using SAS software. I also manage a global team of analytical professionals who help people use SAS software to make smarter decisions based on data.
The principles of experimentation can help you to effectively and efficiently determine what works and doesn’t work in business decisions, identify your most profitable segments, and eliminate noise due to nuisance effects. In this course, you’ll learn about experimentation in business and why experiments are so critical to successful model implementation.
You’ll also learn some important terminology for experimentation. Then, we’ll take a look at incremental response modeling. You will learn to use Enterprise Miner software to fit this useful and interesting class of models and we’ll evaluate and discuss the results. Let’s get started!
Course Curriculum
| 1.0 Experimentation in Business Introduction | |||
| 1.0 Experimentation in Business Introduction | 00:00:00 | ||
| 1.0 Experimentation in Business Objectives | |||
| 1.0 Experimentation in Business Objectives | 00:00:00 | ||
| 1.1a Answering Business Questions | |||
| 1.1a Answering Business Questions | 00:00:00 | ||
| 1.1b Considerations for Formulating Experiments | |||
| 1.1b Considerations for Formulating Experiments | 00:00:00 | ||
| 1.1c Accounting for Variables that Cannot be Controlled | |||
| 1.1c Accounting for Variables that Cannot be Controlled | 00:00:00 | ||
| 1.1d Using Experiments in Business | |||
| 1.1d Using Experiments in Business | 00:00:00 | ||
| 1.2a Learning Terminology for Design of Experiments | |||
| 1.2a Learning Terminology for Design of Experiments | 00:00:00 | ||
| 1.2b Terminology- Response | |||
| 1.2b Terminology- Response | 00:00:00 | ||
| 1.2c Terminology- Factor and Factor Level | |||
| 1.2c Terminology- Factor and Factor Level | 00:00:00 | ||
| 1.2d Terminology- Effect | |||
| 1.2d Terminology- Effect | 00:00:00 | ||
| 1.2e Terminology- Treatment | 00:00:00 | ||
| 1.2e Terminology- Treatment | |||
| 1.2e Terminology- Treatment | 00:00:00 | ||
| 1.2 Think About It | |||
| 1.2 Think About It | 00:00:00 | ||
| 1.2f Terminology- Experimental Unit, Replication, and Power | |||
| 1.2f Terminology- Experimental Unit, Replication, and Power | 00:00:00 | ||
| 1.2g Designing Efficient Experiments | |||
| 1.2g Designing Efficient Experiments | 00:00:00 | ||
| 1.2h Randomization in Experiments | |||
| 1.2h Randomization in Experiments | 00:00:00 | ||
| 1.2i Terminology- Orthogonality | |||
| 1.2i Terminology- Orthogonality | 00:00:00 | ||
| 1.2j Two-Level Full Factorial Coding | |||
| 1.2j Two-Level Full Factorial Coding | 00:00:00 | ||
| 1.2k Factorial Arrangement versus OFAT Tests | |||
| 1.2k Factorial Arrangement versus OFAT Tests | 00:00:00 | ||
| 1.2l Factors, Blocks, and Covariates | |||
| 1.2l Factors, Blocks, and Covariates | 00:00:00 | ||
| 1.2m Other Designed Experiments | |||
| 1.2m Other Designed Experiments | 00:00:00 | ||
| 1.2n Think About It | |||
| 1.2n Think About It | 00:00:00 | ||
| 2.0 Incremental Response Models Introduction | |||
| 2.0 Incremental Response Models Introduction | 00:00:00 | ||
| 2.0 Objectives | |||
| 2.0 Objectives | 00:00:00 | ||
| 2.1a Combining Experimentation with Predictive Modeling | |||
| 2.1a Combining Experimentation with Predictive Modeling | 00:00:00 | ||
| 2.1b Using Data Science to Inform Business Decisions | |||
| 2.1b Using Data Science to Inform Business Decisions | 00:00:00 | ||
| 2.1c Understanding Incremental Response | |||
| 2.1c Understanding Incremental Response | 00:00:00 | ||
| 2.1d Understanding the Role of the Control Group in Incremental Response | |||
| 2.1d Understanding the Role of the Control Group in Incremental Response | 00:00:00 | ||
| 2.1e Explaining the Importance of Incremental Response | |||
| 2.1e Explaining the Importance of Incremental Response | 00:00:00 | ||
| 2.1f Defining Incremental Response | |||
| 2.1f Defining Incremental Response | 00:00:00 | ||
| 2.2a Incremental Response Modeling | |||
| 2.2a Incremental Response Modeling | 00:00:00 | ||
| 2.2b Data Structure for Incremental Response Modeling | |||
| 2.2b Data Structure for Incremental Response Modeling | 00:00:00 | ||
| 2.2c Variable Selection in Incremental Response Modeling | |||
| 2.2c Variable Selection in Incremental Response Modeling | 00:00:00 | ||
| 2.2d Difference Score Model | |||
| 2.2d Difference Score Model | 00:00:00 | ||
| 2.2e Stepwise Regression Model | |||
| 2.2e Stepwise Regression Model | 00:00:00 | ||
| 2.2f Incremental Sales Model | |||
| 2.2f Incremental Sales Model | 00:00:00 | ||
| 2.2g Incremental Response/Sales Model Results | |||
| 2.2g Incremental Response/Sales Model Results | 00:00:00 | ||
| 2.2h Model Diagnostics | |||
| 2.2h Model Diagnostics | 00:00:00 | ||
| 2.2i Incremental Revenue Analysis | |||
| 2.2i Incremental Revenue Analysis | 00:00:00 | ||
| 2.2j Demo- Incremental Response Modeling | |||
| 2.2j Demo- Incremental Response Modeling | 00:00:00 | ||
| Course Notes: Experimentation in Data Science | |||
| Course Notes: Experimentation in Data Science | 00:00:00 | ||
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