Business Analytics 2nd Edition by James Evans ISBN 129209544X 9781292095448

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Product details:
ISBN 10: 129209544X
ISBN 13: 9781292095448
Author: James Evans

provides a comprehensive introduction to the concepts, tools, and techniques of business analytics. The book emphasizes practical application, offering insights into how data analysis can be used to make informed business decisions. It covers key topics such as statistical methods, predictive modeling, optimization, and data visualization, while also highlighting how these methods can be applied in real-world business contexts across various industries. With updated content, examples, and case studies, this edition offers students and professionals the skills needed to effectively analyze business data and drive strategic decision-making.

Business Analytics 2nd Edition Table of contents:

Part I: Introduction to Business Analytics

1. Business Analytics Overview

   • The Role of Analytics in Business
   • Types of Analytics: Descriptive, Predictive, and Prescriptive
   • The Analytics Process
   • Key Challenges in Business Analytics

2. Data and Data Preparation

   • Types of Data: Structured vs. Unstructured
   • Data Cleaning and Transformation
   • Data Quality and Preprocessing Techniques
   • Understanding Data Sources and Types

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Part II: Descriptive Analytics

3. Data Exploration and Visualization

   • Introduction to Data Visualization
   • Descriptive Statistics: Mean, Median, Mode, Variance
   • Using Graphs and Charts for Data Analysis
   • Tools and Software for Data Visualization

4. Summarizing Data and Understanding Distributions

   • Central Tendency and Dispersion
   • Frequency Distributions and Histograms
   • Measures of Shape: Skewness and Kurtosis
   • Understanding Normal and Other Data Distributions

5. Exploratory Data Analysis (EDA)

   • Identifying Patterns and Relationships in Data
   • Techniques for Visualizing Correlation
   • Scatter Plots, Box Plots, and Heatmaps
   • Tools for EDA

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Part III: Predictive Analytics

6. Probability and Statistical Inference

   • Basics of Probability Theory
   • Probability Distributions
   • Sampling and Sampling Distributions
   • Hypothesis Testing and Confidence Intervals

7. Regression Analysis

   • Simple Linear Regression
   • Multiple Linear Regression
   • Model Evaluation and Interpretation
   • Applications of Regression in Business Analytics

8. Classification Models

   • Introduction to Classification Algorithms
   • Logistic Regression
   • Decision Trees and Random Forests
   • Model Performance Metrics (Accuracy, Precision, Recall)

9. Time Series Analysis

   • Forecasting with Time Series Data
   • Decomposition and Trend Analysis
   • Moving Averages and Exponential Smoothing
   • Advanced Time Series Models

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Part IV: Prescriptive Analytics

10. Optimization Models

    • Introduction to Optimization in Business
    • Linear Programming and Constraints
    • Integer and Nonlinear Programming
    • Optimization Applications in Supply Chain, Production, and Finance

11. Simulation Modeling

    • Basics of Simulation Techniques
    • Monte Carlo Simulation
    • Sensitivity Analysis and Scenario Planning
    • Simulation Applications in Risk Management and Operations

12. Decision Analysis

    • Decision Trees and Expected Value
    • Multi-Criteria Decision Making
    • The Role of Sensitivity and Uncertainty in Decision Making
    • Applications in Business Strategy and Risk Assessment

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Part V: Implementing Business Analytics

13. Building and Implementing Analytics Solutions

    • The Analytics Workflow: From Data to Insights
    • Choosing the Right Analytics Tools and Software
    • Implementing and Communicating Results Effectively
    • Case Studies in Business Analytics

14. Ethical and Legal Issues in Business Analytics

    • Privacy and Data Security Concerns
    • Ethical Use of Analytics in Business Decision Making
    • Legal Considerations in Data Analytics

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Part VI: Advanced Topics and Future Trends

15. Big Data and Machine Learning in Business Analytics

    • Understanding Big Data Concepts
    • Introduction to Machine Learning Techniques
    • Big Data Applications in Business Analytics
    • The Future of Business Analytics

16. Business Analytics in Practice

    • Industry Case Studies: Marketing, Finance, Healthcare, Operations
    • Integrating Analytics into Business Strategy
    • Trends and Innovations in Analytics

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James Evans,Business Analytics