Book chapter
THE HAZARDS OF SUBGROUP ANALYSIS IN RANDOMIZED BUSINESS EXPERIMENTS AND HOW TO AVOID THEM
pp.79-91
Contemporary Perspectives in Data Mining, Information Age Publishing-Iap
01 Jan 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Experiments arc ever more widely used in business. Frequently the experimental units arc represented in databases with available covariates, raising the opportunity for subgroup analysis. There are two types of subgroups analyses: hypothesis generation and hypothesis testing. The former is very easy to do, but the latter is difficult. We offer an example of subgroup analysis that shows the pitfalls, and gives rules for avoiding the pitfalls. We also provide a dataset that can be used for classroom exercises.
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Details
- Title
- THE HAZARDS OF SUBGROUP ANALYSIS IN RANDOMIZED BUSINESS EXPERIMENTS AND HOW TO AVOID THEM
- Creators
- B. D. McCullough - Drexel University
- Contributors
- K D Lawrence (Editor)R K Klimberg (Editor)
- Publication Details
- pp.79-91
- Series
- Contemporary Perspectives in Data Mining
- Publisher
- Information Age Publishing-Iap; CHARLOTTE
- Number of pages
- 13
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Identifiers
- 991019170508104721
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- Computer Science, Artificial Intelligence
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- Computer Science, Theory & Methods