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About Statistical Modeling
This document discusses the challenges that arise when statistical modeling results contradict domain expertise or expectations. It notes that statisticians often present results that disagree with what non-statistical audiences, like marketing officers, believe based on experience. The document examines this issue from both practical and theoretical perspectives. It first discusses various types of uncertainties that exist in business contexts and can impact statistical modeling, such as unclear goals, vague or incomplete data definitions, and lack of holistic consideration of uncertainties. It then reviews different sources of statistical uncertainty and how they relate to the fundamental nature of statistical and other models. The conclusion synthesizes these two sections to outline the complex real-world environment in which business modeling occurs.
Detailed Information
| Author: | ['Anonymous PKVCsG'] |
|---|---|
| Publication Year: | 2014 |
| Pages: | 19 |
| Language: | English |
| Format: | |
| Price: | FREE |
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