SAS.Publishing.Basic.Statistics.Using.SAS.Enterprise.Guide.A.Primer.Nov.2007.pdf

Basic Statistics

Using SAS ®

Enterprise Guide ®

a Primer

Geoff Der

Brian S. Everitt

The correct bibliographic citation for this manual is as follows: Der, Geoff, and Brian S. Everitt. 2007.

Basic Statistics Using SAS ® Enterprise Guide ® : A Primer. Cary, NC: SAS Institute Inc.

Basic Statistics Using SAS ® Enterprise Guide ® : A Primer

ISBN 978-1-59994-573-6

For a hard-copy book: No part of this publication may be reproduced, stored in a retrieval system, or

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documentation by the U.S. government is subject to the Agreement with SAS Institute and the restrictions set

forth in FAR 52.227-19, Commercial Computer Software-Restricted Rights (June 1987).

SAS Institute Inc., SAS Campus Drive, Cary, North Carolina 27513.

1st printing, November 2007

SAS ® Publishing provides a complete selection of books and electronic products to help customers use SAS

software to its fullest potential. For more information about our e-books, e-learning products, CDs, and hard-

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Other brand and product names are registered trademarks or trademarks of their respective companies.

Contents

Preface ix

Chapter 1 Introduction to SAS Enterprise Guide 1

1.1 What Is SAS Enterprise Guide? 2

1.2 Using This Book 3

1.3 The SAS Enterprise Guide Interface 4

1.3.1 SAS Enterprise Guide Projects 5

1.3.2 The User Interface 5

1.3.3 The Process Flow 6

1.3.4 The Active Data Set 8

1.4 Creating a Project 9

1.4.1 Opening a SAS Data Set 9

1.4.2 Importing Data 10

1.5 Modifying Data 15

1.5.1 Modifying Variables: Using Queries 15

1.5.2 Recoding Variables 18

1.5.3 Splitting Data Sets: Using Filters 20

1.5.4 Concatenating and Merging Data Sets:

Appends and Joins 21

1.5.5 Names of Data Sets and Variables in SAS and

SAS Enterprise Guide 26

1.5.6 Storing SAS Data Sets: Libraries 27

1.6 Statistical Analysis Tasks 28

1.7 Graphs 30

1.8 Running Parts of the Process Flow 30

iv Contents

Chapter 2 Data Description and Simple Inference 31

2.1 Introduction 32

2.2 Example: Guessing the Width of a Room: Analysis of Room

Width Guesses 32

2.2.1 Initial Analysis of Room Width Guesses Using Simple

Summary Statistics and Graphics 33

2.2.2 Guessing the Width of a Room: Is There Any Difference in

Guesses Made in Feet and in Meters? 40

2.2.3 Checking the Assumptions Made When Using Student’s

t -Test and Alternatives to the t -Test 47

2.3 Example: Wave Power and Mooring Methods 49

2.3.1 Initial Analysis of Wave Energy Data Using Box Plots 50

2.3.2 Wave Power and Mooring Methods: Do Two Mooring

Methods Differ in Bending Stress? 54

2.3.3 Checking the Assumptions of the Paired t -Tests 56

2.4 Exercises 57

Chapter 3 Dealing with Categorical Data 61

3.1 Introduction 61

3.2 Example: Horse Race Winners 62

3.2.1 Looking at Horse Race Winners Using Some Simple

Graphics: Bar Charts and Pie Charts 62

3.2.2 Horse Race Winners: Does Starting Stall Position Predict

Horse Race Winners? 66

3.3 Example: Brain Tumors 68

3.3.1 Tabulating the Brain Tumor Data into a Contingency

Table 69

3.3.2 Do Different Types of Brain Tumors Occur More

Frequently at Particular Sites? The Chi-Square Test 70

3.4 Example: Suicides and Baiting Behavior 71

3.4.1 How Is Baiting Behavior at Suicides Affected by Season?

Fisher’s Exact Test 71

3.5 Example: Juvenile Felons 74

3.5.1 Juvenile Felons: Where Should They Be Tried?

McNemar’s Test 75

3.6 Exercises 74

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