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📊 Business Analytics, 2nd Edition – Complete Table of Contents | James R. Evans

Discover the essential guide to modern business analytics, data-driven decision making, and predictive modeling in Business Analytics, 2nd Edition by James R. Evans. With this comprehensive textbook (ISBN-10: 0321997824, ISBN-13: 9780321997821), you’ll master analytics from the basics of spreadsheets to advanced optimization and simulation techniques. Explore the four pillars of analytics: Foundations, Descriptive, Predictive, and Prescriptive Analytics.

🟦 PART 1: Foundations of Business Analytics

Build a strong foundation in business analytics, understanding key concepts and spreadsheet applications.

1️⃣ Introduction to Business Analytics

• Overview of business analytics

• Role in decision-making

• Types of analytics: descriptive, predictive, prescriptive

2️⃣ Analytics on Spreadsheets

• Basics of Excel and spreadsheet modeling

• Data manipulation and formula techniques

• Practical examples for business problem-solving

🟩 PART 2: Descriptive Analytics

Learn how to explore, visualize, and summarize data for informed decisions.

3️⃣ Visualizing and Exploring Data

• Data visualization techniques

• Charts, graphs, and dashboards

• Identifying trends and patterns

4️⃣ Descriptive Statistical Measures

• Central tendency: mean, median, mode

• Dispersion: variance, standard deviation, range

• Understanding data distributions

5️⃣ Probability Distributions and Data Modeling

• Common probability distributions: normal, binomial, Poisson

• Modeling uncertainty in business contexts

6️⃣ Sampling and Estimation

• Sampling techniques and strategies

• Point and interval estimation

• Confidence intervals and margins of error

7️⃣ Statistical Inference

• Hypothesis testing

• P-values and significance levels

• Applications in business decision-making

🟨 PART 3: Predictive Analytics

Use historical data to forecast and predict future outcomes.

8️⃣ Trendlines and Regression Analysis

• Simple and multiple regression models

• Trendline analysis for business forecasting

9️⃣ Forecasting Techniques

• Time series analysis

• Moving averages and exponential smoothing

• Short-term vs long-term forecasting

🔟 Introduction to Data Mining

• Data mining concepts and applications

• Clustering, classification, and association rules

11️⃣ Spreadsheet Modeling and Analysis

• Advanced Excel modeling

• Scenario and sensitivity analysis

12️⃣ Monte Carlo Simulation and Risk Analysis

• Risk modeling with Monte Carlo simulation

• Decision-making under uncertainty

🟥 PART 4: Prescriptive Analytics

Optimize business decisions using linear and integer programming, and decision analysis.

13️⃣ Linear Optimization

• Formulating linear programming problems

• Simplex method and sensitivity analysis

14️⃣ Applications of Linear Optimization

• Resource allocation and scheduling

• Production and inventory optimization

15️⃣ Integer Optimization

• Integer and binary decision variables

• Applications in logistics and operations

16️⃣ Decision Analysis

• Decision trees and payoff tables

• Risk and utility analysis

🟪 Supplementary Chapters (Online)

• A: Nonlinear and Non-Smooth Optimization

• B: Optimization Models with Uncertainty

📘 Appendix & Glossary

• Essential reference tables

• Key terms for business analytics students

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