SAS Publishing Basic Statistics Using SAS Enterprise Guide A Primer Nov 2007.pdf
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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
Copyright © 2007, SAS Institute Inc., Cary, NC, USA
ISBN 978-1-59994-573-6
All rights reserved. Produced in the United States of America.
For a hard-copy book:
No part of this publication may be reproduced, stored in a retrieval system, or
transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise, without the
prior written permission of the publisher, SAS Institute Inc.
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the vendor at the time you acquire this publication.
U.S. Government Restricted Rights Notice:
Use, duplication, or disclosure of this software and related
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
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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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