Business Analytics Methods, Models, and Decisions (3rd Edition) by James R. Evans

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CHAPTER WISE BOOK SUMMARY

"Business Analytics: Methods, Models, and Decisions" (3rd Edition) by James R. Evans offers a comprehensive exploration of business analytics, focusing on descriptive, predictive, and prescriptive analytics. Below is a chapter-wise summary of the book:

Part 1: Foundations of Business Analytics

 Chapter 1: Introduction to Business Analytics

Introduces the field of business analytics, discussing its importance, evolution, and foundational concepts.

 Chapter 2: Database Analytics

Focuses on data management, including data sets, databases, and techniques for data querying and filtering.

Part 2: Descriptive Analytics

 Chapter 3: Data Visualization

Explores methods for effectively presenting data using various visualization tools and techniques.

 Chapter 4: Descriptive Statistics

Covers statistical measures to summarize and describe data characteristics.

 Chapter 5: Probability Distributions and Data Modeling

Discusses probability concepts and their application in modeling data distributions.

 Chapter 6: Sampling and Estimation

Addresses techniques for sampling data and making estimations about populations.

 Chapter 7: Statistical Inference

Introduces methods for making inferences about populations based on sample data.

Part 3: Predictive Analytics

 Chapter 8: Trendlines and Regression Analysis

Examines techniques for identifying trends and relationships between variables using regression analysis.

 Chapter 9: Forecasting Techniques

Discusses methods for predicting future data points based on historical trends.

 Chapter 10: Introduction to Data Mining

Provides an overview of data mining techniques for discovering patterns in large data sets.

 Chapter 11: Spreadsheet Modeling and Analysis

Focuses on using spreadsheets for modeling and analyzing business scenarios.

 Chapter 12: Simulation and Risk Analysis

Covers simulation methods to assess risk and uncertainty in decision-making.

Part 4: Prescriptive Analytics

 Chapter 13: Linear Optimization

Introduces linear programming techniques for optimizing business decisions.

 Chapter 14: Integer and Nonlinear Optimization

Explores advanced optimization methods involving integer and nonlinear models.

 Chapter 15: Optimization Analytics

Discusses the application of optimization techniques in various business contexts.

Part 5: Making Decisions

 Chapter 16: Decision Analysis

Focuses on frameworks and tools for making informed business decisions.

This structured approach equips readers with the necessary tools and methodologies to effectively analyze data and make informed decisions in various business environments.

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