Description

Book Synopsis
Designed for courses that provide a conceptual and broad-based introduction to econometrics and business analytics, Predictive Analytics for Business Strategy, 1st edition provides future managers with a basic understanding of what data can do in forming business strategy without getting into a taxonomy of models and their statistical properties. Through engaging questions, explanations, and applications, students develop a deeper understanding of the fundamental reasoning behind how and why analysis can generate actionable knowledge and learn to think critically about whether a given analysis has merit or not.

Table of Contents
Chapter 1: The Roles of Data and Predictive Analytics in Business
Chapter 2: Reasoning with Data


Chapter 3: Reasoning from Sample to Population


Chapter 4: The Scientific Method: The Gold Standard for Establishing Causality


Chapter 5: Linear Regression as a Fundamental Descriptive Tool


Chapter 6: Correlation vs. Causality in Regression Analysis


Chapter 7: Basic Methods for Establishing Causal Inference


Chapter 8: Advances Methods for Establishing Causal Inference


Chapter 9: Prediction for a Dichotomous Variable


Chapter 10: Identification and Data Assessment


ISE Predictive Analytics for Business Strategy

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    A Paperback / softback by Jeff Prince

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      Book details

      Publisher McGraw-Hill Education
      Published 4 July 2018
      ISBN-13 9781260084641
      978-1260084641
      ISBN-10 1260084647
      Also in:
      Business, Finance & Law Business and Management

      Description

      Book Synopsis
      Designed for courses that provide a conceptual and broad-based introduction to econometrics and business analytics, Predictive Analytics for Business Strategy, 1st edition provides future managers with a basic understanding of what data can do in forming business strategy without getting into a taxonomy of models and their statistical properties. Through engaging questions, explanations, and applications, students develop a deeper understanding of the fundamental reasoning behind how and why analysis can generate actionable knowledge and learn to think critically about whether a given analysis has merit or not.

      Table of Contents
      Chapter 1: The Roles of Data and Predictive Analytics in Business
      Chapter 2: Reasoning with Data


      Chapter 3: Reasoning from Sample to Population


      Chapter 4: The Scientific Method: The Gold Standard for Establishing Causality


      Chapter 5: Linear Regression as a Fundamental Descriptive Tool


      Chapter 6: Correlation vs. Causality in Regression Analysis


      Chapter 7: Basic Methods for Establishing Causal Inference


      Chapter 8: Advances Methods for Establishing Causal Inference


      Chapter 9: Prediction for a Dichotomous Variable


      Chapter 10: Identification and Data Assessment


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