Book description
Practical Business Analytics Using SAS: A Handson Guide shows SAS users and businesspeople how to analyze data effectively in reallife business scenarios.
The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers handson exercises drawn from real business situations.
The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life.
Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes:
Practical Business Analytics Using SAS: A Handson Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before.
Table of contents
 Cover
 Title
 Copyright
 Dedication
 Contents at a Glance
 Contents
 About the Authors
 Acknowledgments
 Preface

Part 1: Basics of SAS Programming for Analytics
 Chapter 1: Introduction to Business Analytics and Data Analysis Tools
 Chapter 2: SAS Introduction
 Chapter 3: Data Handling Using SAS
 Chapter 4: Important SAS Functions and Procs

Part 2: Using SAS for Business Analytics
 Chapter 5: Introduction to Statistical Analysis
 Chapter 6: Basic Descriptive Statistics and Reporting in SAS

Chapter 7: Data Exploration, Validation, and Data Sanitization
 Data Exploration Steps in a Statistical Data Analysis Life Cycle
 Need for Data Exploration and Validation
 Issues with the RealWorld Data and How to Solve Them
 Understanding and Preparing the Data

Data Exploration, Validation, and Sanitization Case Study: Credit Risk Data
 Importing the Data
 Step 1: Data Exploration and Validation Using the PROC CONTENTS
 Step 2: Data Exploration and Validation Using Data Snapshot
 Step 3: Data Exploration and Validation Using Univariate Analysis
 Step 4: Data Exploration and Validation Using Frequencies
 Step 5: The Missing Value and Outlier Treatment
 Conclusion
 Chapter 8: Testing of Hypothesis

Chapter 9: Correlation and Linear Regression

What Is Correlation?
 Pearson’s Correlation Coefficient (r)
 Variance and Covariance
 Correlation Matrix
 Calculating Correlation Coefficient Using SAS
 Correlation Limits and Strength of Association
 Properties and Limitations of Correlation Coefficient (r)
 Some Examples on Limitations of Correlation
 Correlation vs. Causation
 Correlation Example
 Correlation Summary
 Linear Regression
 Simple Linear Regression
 When Linear Regression Can’t Be Applied
 Simple Regression: Example
 Conclusion

What Is Correlation?
 Chapter 10: Multiple Regression Analysis

Chapter 11: Logistic Regression
 Predicting IceCream Sales: Example
 Nonlinear Regression
 Logistic Regression
 Logistic Regression Using SAS
 SAS Logistic Regression Output Explanation
 Individual Impact of Independent Variables
 Goodness of Fit for Logistic Regression
 Prediction Using Logistic Regression
 Multicollinearity in Logistic Regression
 Logistic Regression Final Check List
 Loan Default Prediction Case Study
 Conclusion
 Chapter 12: TimeSeries Analysis and Forecasting
 Chapter 13: Introducing Big Data Analytics
 Index
Product information
 Title: Practical Business Analytics Using SAS: A Handson Guide
 Author(s):
 Release date: February 2015
 Publisher(s): Apress
 ISBN: 9781484200438
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