Copyright © 2010, SAS Institute Inc. All rights reserved.

Advanced Business Analytics

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Chapter 1 Overview1.1 Overview of Business Analytics

1.2 Software Used in This Course

1.3 Recommended Reading

1.4 Solutions to Student Activities (Polls/Quizzes)

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Chapter 2 Basics of Business Analytics2.1 Overview of Techniques

2.2 Data Management

2.3 Data Difficulties

2.4 SAS Enterprise Miner: A Primer

2.5 Honest Assessment

2.6 Methodology

2.7 Recommended Reading

2.8 Solutions to Student Activities (Polls/Quizzes)

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Chapter 3 SAS Rapid Predictive Modeler3.1 Introduction

3.2 SAS Rapid Predictive Modeler Process Overview

3.3 SAS Rapid Predictive Modeler Model Settings

3.4 SAS Rapid Predictive Modeler Output

3.5 Saving Model Project Data

3.6 Registering the Model

3.7 Scoring

3.8 SAS Rapid Predictive Modeler Methods in SAS Enterprise Miner

3.9 Opening SAS Rapid Predictive Modeler Diagrams in SAS Enterprise Miner

3.10 Modifying SAS Rapid Predictive Modeler Diagrams

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Chapter 4 Predictive Modeling4.1 Introduction to Predictive Modeling

4.2 Predictive Modeling Using Decision Trees

4.3 Predictive Modeling Using Logistic Regression

4.4 Churn Case Study

4.5 A Note about Model Management

4.6 Recommended Reading

4.7 Solutions to Student Activities (Polls/Quizzes)

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Chapter 5 Design of Experiments5.1 Why Experiment?

5.2 Introduction

5.3 Multi-Factor Experiments

5.4 Orthogonality and Blocking

5.5 Business Experiments with Continuous Responses

5.6 Recommended Reading

5.7 Solutions to Student Activities (Polls/Quizzes)

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Chapter 6 Segmentation6.1 Introduction

6.2 Cluster Segmentation

6.3 Market Basket Analysis

6.4 Recommended Reading

6.5 Solutions to Student Activities (Polls/Quizzes)

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Chapter 7 Forecasting7.1 Introduction

7.2 Time Series Characteristics and Components

7.3 Introduction to SAS Forecast Studio

7.4 Time Series Regression Models

7.5 Time Series Data and Hierarchical Data Structure

7.6 Recommended Reading

7.7 Solutions to Student Activities (Polls/Quizzes)

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Appendix A Introduction to Statistical ConceptsA.1 Fundamental Statistical Concepts

A.2 Picturing Distributions

A.3 Confidence Intervals for the Mean

A.4 Hypothesis Testing

A.5 Two-Sample t Tests

A.6 One-Way ANOVA

A.7 ANOVA Post Hoc Tests

A.8 Two-Way ANOVA with Interactions

A.9 Checking Linear Regression Assumptions

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Appendix B A Primer of Time Series Forecasting ModelsB.1 A Primer of Time Series Forecasting Models

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SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright © 2012 SAS Institute Inc. Cary, NC, USA. All rights reserved. Prepared 11JUN2012.