SPSS 13.0 BRIEF GUIDE

Download

Page 1

SPSS® 13.0 Brief Guide

Page 2

For more information about SPSS®softwareproducts,pleasevisitourWeb site at http://www.spss.com or contact SPSS Inc.

233 South Wacker Drive, 11th Floor Chicago, IL 60606-6412 Tel: (312) 651

-3000

Fax: (312) 651-3668 SPSS is a registered trademark and the other product names are the trademarks of SPSS Inc. for its proprietary

computer soft

ware. No material describing such software may be produced or distributed without the written permission of the owners of the trademark and license rights in the software and the copyrights in the published materials.

The SOFTWARE a

nd documentation are provided with RESTRICTED RIGHT S. Use, duplication, or disclosure by the Government is subject to restrictions as set forth in subdivision (c) (1) (ii) of The Rights in Technical Data and Computer Software clause at 52.227-7013. Contractor/manufacturer is SPSS Inc., 233 South Wacker Drive, 11thFloor,C

hicago, IL 60606-6412.

General notice: Other product names mentioned herein are used for identification purposes only and may b e trademarks of their respective companies.

TableLook is

a trademark of SPSS Inc. Windows is a registered trademark of Microsoft Corporation. DataDirect, DataDirect Connect, INTERSOLV, and SequeLink are registered trademarks of DataDirect Technologie

OLS, and LEADVIEW are registered trademarks of LEAD Technologies, Inc. Sax Basic is a trademark of Sax Software Corporation. Copyright © 1993–2004 by Polar Engineering and Consulting. All rights reserved. Portions of t

his product were based on the work of the FreeType Team (http://www.freetype.org). A portion of the SPSS software contains zlib technology. Copyright © 1995–2002 by Jean-loup Gailly and Mark Adler. The zlib software is provided “as is,” without express or implied warranty. A portion of t

he SPSS software contains Sun Java Runtime libraries. Copyright © 2003 by Sun Microsystems, Inc. All rights reserved. The Sun Java Runtime libraries include code licensed from RSA Security, Inc. Some portions of the libraries are licensed from IBM and are available at http://oss.software.ibm.com/icu4j/.

SPSS® 13.0 B r

United States of America.

No part of this publication m ay be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publis

her.

ISBN 0-13-154242-7

Page 3

SPSS 13.0

Preface

The SPSS® 13.0 Brief Guide provides a set of tutorials designed to acquaint you with the va tutorials in sequence or turn to the topics for which you need additional information. You can use this guide as a supplement to the online tutorial that is included with the SPSS B found here.

rious components of the SPSS system. You can work through the

ase 13.0 system or ignore the online tutorial and start with the tutorials

SPSS 13.0 almost any type of file and use them to generate tabulated reports, charts, and plots of distributions and trends, descriptive statistics, and complex statistical analyses.

SPSS mak convenient for the experienced user. Simple menus and dialog box selections make it possible to perform complex analyses without typing a single line of command syntax entering data and browsing the working data file.

Internet Resources

The SPSS Web site (http://www.spss.com) offers answers to frequently asked questi files and other useful information.

In addition, the SPSS USENET discussion group (not sponsored by SPSS) is ope comp.soft-sys.stat.spss. It deals with computer, statistical, and other operational issuesrelatedtoSPSSsoftware.

is a comprehensive system for analyzing data. SPSS can take data from

es statistical analysis more accessible for the beginner and more

. The Data Editor offers a simple and efficient spreadsheet-like facility for

ons about installing and running SPSS software and provides access to data

ntoanyoneinterestedinSPSSproducts. TheUSENETaddressis

iii

Page 4

You can also subscribe to an e-mail message list that is gatewayed to the USENET group. To subscribe, send an e-mail message to [email protected]. The text of the e-mail me

ssage should be:

subscribe SPSSX-L firstname lastname. You can then

post messages to the list by sending an e-mail message to [email protected].

Additional Publications

For additional information about the features and operations of SPSS Base 13.0, you can cons

ult the SPSS Base 13.0 User’s Guide, which includes information on standard graphics. Examples using the statistical procedures found in SPSS Base 13.0 are provided in the Help system, installed with the software. Algorithms used in the statistic

al procedures are available on the product CD-ROM.

In addition, beneath the menus and dialog boxes, SPSS uses a command language. Some extended features of the system can be accessed only via command syntax. (Those fea

tures are not available in the Student Version.) Complete command syntax is documented in the SPSS 13.0 Command Syntax Reference, available in PDF form from the Help menu.

Individu

als worldwide can order additional product manuals directly from SPSS Inc. For telephone orders in the United States and Canada, call SPSS Inc. at 800-543-2185. For telephone orders outside of North America, contact your local

listed on the SPSS Web site at http://www.spss.com/worldwide.

office,

The SPSS Statistical Procedures Companion, by Marija Norušis, has been published by Prentice Hall. It contains overviews of the procedures in the SPSS Base, pl

us Logistic Regression and General Linear Models. A Statistical Procedures

Companion covering advanced procedures is forthcoming.

SPSS Options

The following options are available as add-on enhancements to the full (not Student

n) SPSS Base system:

Versio

SPSS Re

gression Models™

provides techniques for analyzing data that do not fit traditional linear statistical models. It includes procedures for probit analysis, logistic regression, weight estimation, two-stage least-squares regression, and general

ear regression.

nonlin

Page 5

SPSS Advanced Models™ focuses on techniques often used in sophisticated

experimental and biomedical research. It includes procedures for general linear models (GLM)

, linear mixed models, variance components analysis, loglinear analysis, ordinal regression, actuarial life t ables, Kaplan-Meier survival analysis, and basic and extended Cox regression.

™

SPSS Tables

creates a variety of presentation-quality tabular reports, including

complex stub-and-banner tables and displays of multiple response data.

SPSS Trends™ performs comprehensive forecasting and time series analyses with

multiple cu

rve-fitting models, smoothing models, and methods for estimating

autoregressive functions.

SPSS Categories® performs optimal scaling procedures, including correspondence

analysis.

SPSS Conjoint™ performs conjoint analysis. SPSS Exact Tests™ calculates exact p values for statistical tests when small or very

unevenly d

SPSS Missing Value Analysis™ describes patterns of missing data, estimates means

istributed samples could make the usual tests inaccurate.

and other statistics, and imputes values for missing observations.

SPSS Maps™

turns your geographically distributed data into high-quality maps with symbols, colors, bar charts, pie charts, and combinations of themes to present not only what is happening but where it is happening.

SPSS Comp

lex Samples™

allows survey, market, health, and public opinion researchers, as well as social scientists who use sample survey methodology, to incorporate their complex sample designs into data analysis.

SPSS Clas

sification Tree™

creates a tree-based classification model. It classifies cases into groups or predicts values of a dependent (target) variable based on values of independent (predictor) variables. The procedure provides validation tools for explora

tory and confirmatory classification analysis.

The SPSS family of products also includes applications for data entry, text analysis, classification, neural networks, and flowcharting.

Page 6

Training Seminars

SPSS Inc. provides both public and onsite training seminars for SPSS. All seminars feature hands-on workshops. SPSS seminars will be offered in major U.S. and European cit your local office, listed on the SPSS Web site at http://www.spss.com/worldwide.

ies on a regular basis. For more informationontheseseminars,contact

Technical Support

The services of SPSS Technical Support are available to registered customers of SPSS. (Stud for the Student Version. For more information, see “Technical Support for Students” on p. vii.) Customers may contact Technical Support for assistance in using SPSS products o reach Technical Support, see the SPSS Web site at http://www.spss.com, or contact your local office, listed on the SPSS Web site at http://www.spss.com/worldwide.Be prepared

ent Version customers should read the special section on technical support

r for installation help for one of the supported hardware environments. To

to identify yourself, your organization, and the serial number of your system.

Tell Us Your Thoughts

Your comments are important. Please let us know about your experiences with SPSS products. We especially like to hear about new and interesting applications using the SPSS Attn: Director of Product Planning, 233 South Wacker Drive, 11th Floor, Chicago IL 60606-6412.

system. Please send e-mail to [email protected], or write to SPSS Inc.,

SPSS 13.0 for Windows Student Version

The SPSS 13.0 for Windows Student Version is a limited but still powerful version of the SPSS Base 13.0 system.

Capabi

lity

The Stu the full SPSS Base system, including:

 Spreadsheet-like Data Editor for entering, modifying, and viewing data files.

dent Version contains all of the important data analysis tools contained in

Page 7

 Statistical procedures, including t tests, analysis of variance, and crosstabulations.  Interactive graphics that allow you to change or add chart elements and variables

dynamically

 Standard hi

; the changes appear as soon as they are specified.

gh-resolution graphics for an extensive array of analytical and

presentation charts and tables.

Limitation

Created for

classroom instruction, the Student Version is limited to use by students and instructors for educational purposes only. The Student Version does not contain all of the functions of the SPSS Base 13.0 system. The following limitations apply to the SPSS 13.

 Data files  Data files

0 for Windows Student Version:

cannot contain more than 50 variables.

cannot contain more than 1,500 cases. SPSS add-on modules (such as Regression Models or Advanced Models) cannot be used with the Student Version.

 SPSS command syntax is not available to the user. This means that it is not

possible t

o repeat an analysis by saving a series of commands in a syntax or “job”

file, as can be done in the full version of SPSS.

 Scripting and automation are not available to the user. This means that you

cannot create scripts that automate tasks that you repeat often, as can be done in the full

version of SPSS.

Technical Support for Students

Students should obtain technical support from their instructors or from local support staff identified by their instructors. Technical support from SPSS for the SPSS 13.0 Student V

ersion is provided only to instructors using the system for classroom

instruction.

Before seeking assistance from your instructor, please write down the information

describ

ed below. Without this information, your instructor may be unable to assist

you:

 The type of PC you are using, as well as the amount of RAM and free disk

space yo

 The ope

uhave.

rating system of your PC.

vii

Page 8

 A clear description of what happened and what you were doing when the problem

occurred. If

possible, please try to reproduce the problem with one of the sample

data files provided with the program.

 The exact wording of any error or warning messages that appeared on your screen.  How you tried to solve the problem on your own.

Technical Su

Instructor

pport for Instructors

s using the Student Version for classroom instruction may contact SPSS Technical Support for assistance. In the United States and Canada, call SPSS Technical Support at 312-651-3410, or send an e-mail to [email protected].Please include you

r name, title, and academic institution.

Instructors outside of the United States and Canada should contact your local SPSS

office,listedontheSPSSWebsiteathttp://www.spss.com/worldwide.

viii

Page 9

Contents

1 Introducti

Sample Fil

Starting S

Variable D

OpeningaDataFile............................................ 3

RunninganAnalysis .......................................... 7

ViewingResults ............................................. 10

CreatingCharts.............................................. 11

ExitingSPSS................................................ 13

on 1

es................................................. 1

PSS ............................................... 2

isplayinDialogBoxes.............................. 3

2 Using the Help System 15

HelpContentsTab............................................ 16

HelpIndexTab.............................................. 17

DialogBoxHelp............................................. 18

StatisticsCoach............................................. 19

CaseStudies ............................................... 27

3 Reading Data 29

BasicStructureofanSPSSDataFile ............................. 29

ReadinganSPSSDataFile..................................... 30

ReadingDatafromSpreadsheets................................ 31

ReadingDatafromaDatabase.................................. 34

Page 10

ReadingDatafromaTextFile................................... 41

SavingData ................................................ 49

4UsingtheDa

EnteringNumericData........................................ 51

EnteringStringData.......................................... 54

DefiningData............................................... 56

AddingaVariableLabel.................................... 56

ChangingVariableTypeandFormat........................... 57

Adding Valu

AddingValueLabelsforStringVariables....................... 60

UsingValueLabelsforDataEntry ............................ 61

Handling Mi

MissingValuesforaNumericVariable......................... 63

MissingValuesforaStringVariable........................... 65

Copying and

Defining Variable Properties for Categorical Variables . . . . . . . . . . . . . 72

5 Examining S

ta Editor 51

eLabelsforNumericVariables..................... 58

ssingData..................................... 62

PastingValueAttributes.......................... 66

ummary Statistics for Individual

Variables 79

Level of Me

Summary Me

SummaryMeasuresforScaleVariables........................... 83

asurement ........................................ 79

asuresforCategoricalData.......................... 80

Charts for C

HistogramsforScaleVariables.............................. 86

ategoricalData................................. 81

Page 11

6 Working with

UsingtheViewer ............................................ 89

UsingthePivotTableEditor .................................... 92

AccessingOutputDefinitions................................ 92

PivotingTables .......................................... 93

Creating and

EditingTables ........................................... 98

HidingRowsandColumns................................. 100

Changing Dat

TableLooks................................................ 102

UsingPredefinedFormats................................. 102

Customizing

ChangingtheDefaultTableFormats.......................... 105

CustomizingtheInitialDisplaySettings ....................... 107

Displaying Va

UsingResultsinOtherApplications ............................. 111

PastingResultsasRichText ............................... 112

Pasting Resul

PastingResultsasText ................................... 115

Exporting Results to Microsoft Word, PowerPoint, and Excel Files . . . 116 Exporting Resu

Output 89

DisplayingLayers.............................. 96

aDisplayFormats............................. 100

TableLookStyles .............................. 103

riableandValueLabels......................... 109

tsasMetafiles............................... 113

ltstoHTMLandTextFormats................... 123

7 Creating and Editing Charts 127

Chart Creati

Chart Editin

onBasics........................................ 127

gBasics......................................... 130

Selecting Ch

UsingthePropertiesWindow .............................. 132

ChangingBarColors ..................................... 133

Formatting Nu

artElements.................................. 131

mbersinTickLabels .......................... 135

Page 12

EditingText............................................ 137

DisplayingandEditingDataValueLabels...................... 138

Using Templa

DefiningChartOptions.................................... 145

Other Exam pl

PieChart.............................................. 149

GroupedScatterplot ..................................... 161

tes ........................................ 141

es ............................................ 149

8 Working with

PastingSyntax............................................. 171

EditingSyntax.............................................. 174

TypingSyntax.............................................. 175

SavingSyntax.............................................. 176

OpeningandRunningaSyntaxFile.............................. 176

9 Modifying

CreatingaCategoricalVariablefromaScaleVariable................ 177

ComputingNewVariables..................................... 183

UsingFunctionsinExpressions............................. 185

UsingConditionalExpressions.............................. 187

ComputingVariableswithMissingValues......................... 189

WorkingwithDatesandTimes................................. 194

Calculating t he Length of Time Between Two Dates . . . . . . . . . . . . . . 196

AddingaDurationtoaDate................................ 200

Data Values 177

Syntax 171

xii

Page 13

10 Sorting and S

SortingData............................................... 205

Split-FileProcessing......................................... 206

SortingCasesforSplit-FileProcessing ....................... 209

TurningSplit-FileProcessingOnandOff ...................... 209

SelectingSubsetsofCases.................................... 210

SelectingCasesBasedonConditionalExpressions.............. 211

SelectingaRandomSample ............................... 211

Selecting a T

UnselectedCases....................................... 214

Case Se lecti

electing Data 205

imeRangeorCaseRange....................... 212

onStatus........................................ 214

11 Additional Statistical Procedures 217

SummarizingData........................................... 217

Frequencies............................................ 218

Explore ............................................... 220

MoreaboutSummarizingData.............................. 222

Comparing M

Means................................................ 223

Paired-SamplesTTest.................................... 224

MoreaboutComparingMeans ............................. 226

ANOVAModels............................................. 226

UnivariateAnalysisofVariance............................. 226

Correlatin

Bivariate Co

PartialCorrelations ...................................... 228

Regression A

Linear Regre

eans .......................................... 222

gVariables ........................................ 228

rrelations.................................... 228

nalysis......................................... 230

ssion....................................... 230

xiii

Page 14

NonparametricTests ........................................ 231

Chi-Square ............................................ 231

Time Se ries A

Exponential

nalysis......................................... 233

Smoothing ................................... 234

Index 239

xiv

Page 15

Chapter

Introductio

This guide provides a set of tutorials designed to acquaint you with the various components of the SPSS system. You can work through the tutorials in sequence or turn to the you to perform useful analyses on your data using SPSS.

This chapter will introduce you to the basic environment of SPSS and demonstrate atypicals then produce a simple statistical summary and a chart. In the process, you will learn the roles of the primary windows within SPSS and will see a few features that smooth the way wh

More detailed instruction about many of the topics touched upon in this chapter will follow in later chapters. Here, wehopetogiveyouabasicframeworkfor understa

topics for which you need additional information. The goal is to enable

ession. We will run SPSS, retrieve a previously defined SPSS data file, and

en you are running analyses.

nding and using SPSS.

Sample Files

Most of the examples presented here use the data file demo.sav. Thisdatafileis

ious survey of several thousand people, containing basic demographic and

a fictit consumer information.

All sample files used in these examples are located in the folder in which SPSS is

ed or in the tutorial\sample_files folder within the SPSS installation folder.

install

Page 16

Chapter 1

Starting SPS

To start SPS

E From the Wi

Programs

SPSS for Windows

To start SPSS for Windows Student Version:

E From the Windows Start menu choose:

Programs

SPSS for Windows Student Version

When you start a session, you see the Data Editor window.

Figure 1-1

Data Editor window (Data View)

S: ndows Start menu choose:

Page 17

Variable Display in Dialog Boxes

Either variable names or longer variable labels will appear in list boxes in dialog boxes. Additionally, variables in list boxes can be ordered alphabetically or by their position in

In this guide, we will display variable labels in alphabetical order within list boxes. For a new user of SPSS, this provides a more complete description of variables in an easy-to-

Since the default setting within SPSS is to display variable labels in file order, we will change this before accessing data.

E From the menus choose:

Edit

Options..

the file.

follow order.

Introduction

Select Dis

E Also selec E Click OK,a

play labels

Alphabetical.

nd then click

Opening a Data File

Before you can analyze data, you need some data to analyze.

To open a data file:

E From the menus choose:

File

Open

Data...

in the Variable Lists group on the General tab.

OK to confirm the change.

Page 18

Chapter 1

Alternatively, you can use the Open File button on the toolbar.

Figure 1-2

Open File too

lbar button

This opens the Open File dialog box.

Figure 1-3

Open File di

alog box

By default, SPSS-format data files (.sav extension) are displayed. You can display other file formats using the Files of Type drop-down list.

By default, data files in the folder (directory) in which SPSS is installed are displayed. The files for this guide are located in the folder in which SPSS is installed or in the tutorial\sample_files folder within the SPSS installation folder.

E Double-click the tutorial folder. E Double-click the sample_files folder. E Click the file demo.sav in the files list box (or just demo if file extensions are not

displayed).

Page 19

Figure 1-4

Sample_files folder displayed in Open File dialog box

E ClickOpentoopentheSPSSdatafile.

Figure 1-5

Variable labels

Introduction

ThedatafileisdisplayedintheDataEditor.Ifyouputthemousecursoronavariable

the column headings), a more descriptive variable label is displayed if one has

name ( been defined for that variable.

Page 20

Chapter 1

By default, the actual d ata values are displayed. To display labels:

E From the menus choose:

View

Value Labels

Alternatively, you can use the Label tool on the toolbar.

Figure 1-6

Value Labels

tool

Descriptive value labels are now displayed. This makes it easier to interpret the responses.

Figure 1-7

Value labels displayed in the Data Editor

Page 21

Introduction

Running an An

The Analyze categories. Most of the categories are followed by an arrow, which indicates that there are several analysis procedures available within the category; they will appear on a submenu whe

We’ll start with a simple frequency table (table of counts).

E From the menus choose:

Analyze

Descriptive Statistics

Frequencies...

This opens the Frequencies dialog box.

Figure 1-8

Frequencies dialog box

alysis

menu contains a list of general reporting and statistical analysis

n the category is selected.

Page 22

Chapter 1

Select (click) the variable Income category.

Figure 1-9

Variable lab

els and names in the Frequencies dialog box

A more complete description of each variable pops up when the cursor is over it. The variable name (in square brackets) is inccat, and it has the variable label Income

Viewing Results

Figure 1-1

Viewer win

dow

Results are displayed in the Viewer window.

You can quickly go to any item in the Viewer simply by selecting it in the outline pane.

E Click Income category.

Page 25

Figure 1-13

Frequency table of income categories

Introduction

Creati

kes you directly to the frequency table for income categories. This frequency

This ta table shows the number and percentage of people in each income category.

ng Charts

gh some statistical procedures can create high-resolution charts, you can also

Althou use the Graphs menu to create charts.

For example, you could create a chart that shows the relationship between wireless

one service and PDA (personal digital assistant) ownership.

teleph

E From t

he menus choose:

Graphs

Bar...

Click Clustered and then click Define.

Page 26

Chapter 1

Figure 1-14

Define Clustered Bar dialog box

E Scro

ll down the source variable list and select Wireless service [wireless] as the

Category Axis variable.

E Select Owns PDA [ownpda] as the Define Clusters By variable. E Click OK to create the chart.

Page 27

Figure 1-15

Bar chart displayed in Viewer window

Introduction

Exitin

The bar

chart is displayed in the Viewer. It shows that people with wireless phone

service are far more likely to have PDAs than people without wireless service.

You can edit charts and tables by double-clicking on them in the contents pane of

the View

er window, and you can copy and paste your results into other applications.

Those topics will be covered later.

g SPSS

To exit

E From t

File

Click No if you get an alert asking if you want to save your results.

SPSS:

he menus choose:

Exit

Page 28

Page 29

Chapter

Using the Hel

Help is available in a number of different ways, including:

Help menu. EverywindowhasaHelpmenuonthemenubar.TheTopicsmenuitem

provides a find topics. The Tutorial menu item provides access to the introductory tutorial.

Dialog box Help buttons. Most dialog boxes have a Help button that takes you directly

to a Help to links to related topics.

Pivot table context menu Help. Right-click on terms in an activated pivot table in

the Viewe of the terms.

Statistics Coach. The Statistics Coach item on the Help menu provides a wizard-like

method fo

ccess to the Help system, where you can use the Contents and Index tabs to

pic for that dialog box. The Help topic provides general information and

randselect

r finding the right statistical or charting procedure for what you want to do.

What’s This? from the context menu to display definitions

p System

Case Studies. The Case Studies item on the Help menu provides hands-on examples

of how to create various types of statistical analyses and interpret the results. The sample d the examples to see exactly how the results were produced.

This chapter uses the files demo.sav and bhelptut.spo.

ata files used in the examples are also provided so that you can work through

Page 30

Chapter 2

Help Content

The Topics i

E From the men

Help

Topics

Figure 2-1

Help Cont ent

sTab

tem on the Help menu opens a Help window.

us choose:

stab

The Contents tab in the left pane of the Help window is an expandable and collapsible table of contents. It is most useful if you’re looking for general information or are unsure of what index term to use to find what you’re looking for.

Page 31

Help Index Ta

Figure 2-2

Help Index tab

Using the Help S

ystem

E Click the Index tab in the left pane of the Help window.

The Ind The Index tab is organized in alphabetical order, just like a book index. It uses incremental search to find what you’re looking for.

ex tab provides a searchable index that makes it easy to find specific topics.

Page 32

Chapter 2

For example, you can:

E Type med.

Figure 2-3

Incremental

index search

The index scrolls to and highlights the first index entry that starts with these letters, which is median.

Dialog Box Help

Most dialog boxes have a H elp button that displays a Help topic about what the dialog box does and how to do it.

E From the menus choose:

Analyze

Descriptive Statistics

Frequencies...

Page 33

Click Help.

Figure 2-4

Dialog box He

lp topic

Using the Help S

ystem

In this example, the Help topic describes the purpose of the Frequencies procedure andprovidesanexample.

Statistics Coach

The Statistics Coach can help to guide you through the process of finding the procedure that you want to use.

E From the menus choose:

Help

Statistics Coach

Page 34

Chapter 2

Figure 2-5

Statistics Coach, first step

The Statistics Coach presents a series of questions designed to find the appropriate procedure. The first question is simply “What do you want to do?”

For example, if you want to summarize data:

E Select Summarize, describe, or present data. E Then click Next.

Page 35

Figure 2-6

Data type selection

Using the Help S

ystem

The next question asks about the type of data you want to summarize. If you’re unsure, each choice displays different examples.

E Select Continuous, numeric data (interval, ratio).

Page 36

Chapter 2

Figure 2-7

Selecting a different data type

The example changes to reflect your choice. If you’re still unsure, you can:

E Click More Examples.

A new example of the same data type is displayed. If the examples don’t provide enough information, you can:

E Click Help.

Page 37

Figure 2-8

Statistics Coach Help topic

Using the Help S

ystem

In this example, the Help topic defines the different data types.

E Close the Help window. E Select Data in categories (nominal, ordinal) and click Next.

Page 38

Chapter 2

Select Tables and numbers and click Next.

Figure 2-9

Selecting ta

bles or charts

Page 39

Select Individual case listings within categories.

Figure 2-10

Statistics C

oach, final step

Using the Help S

ystem

When th

e Statistics Coach has enough information, the

Next button changes to Finish.

Page 40

Chapter 2

When you click Finish, the dialog box for the selected procedure opens automatically, and a Help topic for the procedure is also displayed.

Figure 2-11

Dialog box and Help topic

This is a custom Help topic, based on your selections in the Statistics Coach. Since some dialog boxes perform numerous functions, more than one path in the Statistics Coach may lead to the same dialog box, but the instructions in the Help topic may be different.

E Click Tell me more in the Help topic to get more detailed information.

Page 41

Figure 2-12

“Tell me m ore” Help topic

Using the Help S

ystem

Case St

E Righ

This He the selected procedure.

lp topic provides detailed information on the data type(s) appropriate for

udies

Case st in the examples are installed with SPSS, so you can follow along, performing the same analysis—from opening the data source and selecting variables for analysis to inter

To acc

right-click on the frequency table for Gender.

udies provide comprehensive overviews of each procedure. Data files used

preting the results.

ess the case studies:

t-click on any pivot table created by a procedure. For example, you can

Page 42

Chapter 2

Figure 2-13

Accessing the case studies

E Select Case Studies on the pop-up context menu.

Case studies are not available for all procedures. The Case Studies choice on the context menu will appear only if the feature is available for the procedure that created the selected pivot table.

Page 43

Reading Data

Data can be entered directly into SPSS, or it can be imported from a number of differen spreadsheet applications, such as Microsoft Excel, database applications, such as Microsoft Access, and text files are all discussed in this chapter.

Basic Structure of an SPSS Data File

t sources. The processes for reading data stored in SPSS data files,

Chapter

Figure 3-1

Data Edito

SPSS data files are organized by cases (rows) and variables (columns). In this data file, cases represent individual respondents to a survey. Variables represent each question asked in the survey.

Page 44

Chapter 3

ReadinganSP

SPSS data fi demo.sav, an example file that is installed with the product:

E From the menus choose:

File

Open

Data...

Make sure that SPSS (*.sav) is selected in the Files of Type drop-down list.

Figure 3-2

Open File dialog box

SS Data File

les, which have a .sav file extension, contain your saved data. To open

E Navigate to the sample_files folder. E Select demo.sav and click Open.

Page 45

The data are now displayed in the Data Editor.

Reading Data

Figure 3-3

Opened data f

ile

Reading Data from Spreadsheets

Rather than typing all of your data directly into the Data Editor, you can read data from applications such as Microsoft Excel. You can also read column headings as variable names.

E From the menus choose:

File

Open

Data...

Page 46

Chapter 3

Select Excel (*.xls) from the Files of Type drop-down list.

Figure 3-4

Open File dia

E Select demo.xls and click Open to read this spreadsheet.

log box

The Opening Excel Data Source dialog box is displayed, allowing you to specify whether variable names are to be included in the spreadsheet, as well as the cells that you want to import. In Excel 5 or later, you can also specify which worksheets youwanttoimport.

Figure 3-5

Opening Excel Data Source dialog box

Page 47

Make sure that Read variable names from f irst row of data is selected. This option reads column headings as variable names.

Reading Data

If the column

headings do not conform to the SPSS variable-naming rules, they are converted into valid variable names and the original column headings are saved as variable labels. If you want to import only a portion of the spreadsheet, specify the range of cel

E Click OK to

Thedatanow

ls to be imported in the Range text box.

read the Excel file.

appear in the Data Editor, with the column headings used as variable names. If you’re using a spreadsheet application other than Excel or Lotus, you should be able to export your data to a supported format that can then be read into SPSS.

Figure 3-6

Imported Excel data

Page 48

Chapter 3

Reading Data

Data from da database that uses ODBC (Open Database Connectivity) drivers can be read directly by SPSS after the drivers are installed. ODBC drivers for many database formats are supplied on vendors. One of the most common database applications, Microsoft Access, is discussed in this example.

E From the menus choose:

File

Open Datab

New Query.

Figure 3-7

Database W izard Welcome dialog box

from a Database

tabase sources are easily imported using the Database Wizard. Any

the installation CD. Additional drivers can be obtained from third-party

ase

E Select MS Access Database from the list of data sources and click Next.

Page 49

Reading Data

If MS Access Database is not listed here, you need to run Microsoft Data Access Pack.exe, which can be found in the Microsoft Data Access Pack folder on the CD.

Figure 3-8

ODBC Driver Login di alog box

E Click Browse to navigate to the Access database file that you want to open.

Figure 3-9

Open File dialog box

E Selec E Click O

t demo.mdb and click

in the login dialog box.

Open to continue.

Page 50

Chapter 3

In the next step, you can specify the tables and variables that you want to import.

Figure 3-10

Select Data s

tep

E Drag the entire demo table to the Retrieve Fields in This Order list. E Click Next.

Page 51

In the next step, you select which records (cases) to import.

Reading Data

Figure 3-11

Limit Retrie

ved Cases step

If you do not want to import all cases, you can import a subset of cases (for example, males older than 30), or you can import a random sample of cases from the data source. For large data sources, you may want to limit the number of cases to a small, representative sample to reduce the processing time.

E Click Next to continue.

Page 52

Chapter 3

If you are in distributed mode, connected to a remote server (available with SPSS Server), the next step allows you to aggregate the data before reading it into SPSS.

Figure 3-12

Aggregate Data step

You can also aggregate data after reading it into SPSS, but pre-aggregating may save time for large data sources.

E For this example, you don’t need to aggregate the data. If you see this step in the

Database Wizard, click

Next.

Page 53

Reading Data

Field names are used to create variable names. If necessary, the names are converted to valid variable names. The original field names are preserved as variable labels. You can also

Figure 3-13

Define Variables step

change the variable names before importing the database.

E Click the Recode to Numeric cell in the Gender field. This option converts string

variables to integer variables and retains the original value as the value label for the new variable.

E Click Next to continue.

If you are in distributed mode, connected to a remote server (available with SPSS Server), the next step allows you sort the data before reading it into SPSS.

Page 54

Chapter 3

You can also sort data after reading it into SPSS, but presorting may save time for largedatasources.

E For this example, you don’t need to sort the data. If you see this step in the Database

Next.

Wizard, cli

The SQL state

ment created from your selections in the Database Wizard appears in

the Results step. This statement can be executed now or saved to a file for later use.

Figure 3-14

Results ste

E Click Finish to import the data.

Page 55

Reading Data

All of the data in the Access database that you selected to import are now available in theSPSSDataEditor.

Figure 3-15

Data imported from an Access database

Readin

gDatafromaTextFile

les are another common source of data. Many spreadsheet programs and

Text fi databases can save their contents in one of many text file formats. Comma or tab-delimited files refer to rows of data that use commas or tabs to indicate each

ble. In this example, the data are tab delimited.

varia

Page 56

Chapter 3

From the menus choose:

File

Read Text Data...

Choose Text (*.txt) from the Files of Type list.

Figure 3-16

Open File dialog box

E Select demo.txt and click Open to read the selected file.

Page 57

Reading Data

The Text Import Wizard guides you through the process of defining how the specified text file should be interpreted.

Figure 3-17

Text Import Wizard - Step 1 of 6

E In Step 1, you can choose a predefined format or create a new format in the wizard.

Select No to indicate that a new format should be created.

E Click Next to continue.

Page 58

Chapter 3

As stated earlier, this file uses tab-delimited formatting. Also, the variable names aredefinedonthetoplineofthisfile.

Figure 3-18

Text Import Wizard - Step 2 of 6

E Select Delimited to indicate that the data use a delimited formatting structure. E Select Yes to indicate that variable names should be read from the top of the file. E Click Next to continue.

Page 59

Type 2 in the top section of next dialog box to indicate that the first row of data starts on the second line of the text file.

Figure 3-19

Text Import Wizard - Step 3 of 6

Reading Data

E Keepthe default values for the remainder of this dialog box, and click Next to continue.

Page 60

Chapter 3

The Data preview in Step 4 provides you with a quick way to ensure that your data are being properly read by SPSS.

Figure 3-20

Text Import Wizard - Step 4 of 6

E Select Tab and deselect the other options. E Click Next to continue.

Page 61

Reading Data

Because the variable names may have been truncated to fit SPSS formatting requirements, this dialog box gives you the opportunity to edit any undesirable names.

Figure 3-21

Text Import Wizard - Step 5 of 6

Data types can be defined here as well. For example, it’s safe to assume that the income variable is meant to contain a certain dollar amount.

To change a data type:

E Under Data preview, select the variable you want to change, which is Income in

this case.

Page 62

Chapter 3

Select Dollar from the Data format drop-down list.

Figure 3-22

Change the da

E Click Next to continue.

ta type

Page 63

Figure 3-23

Text Import Wizard - Step 6 of 6

Reading Data

E Leave the default selections in this dialog box, and click Finish to import the data.

Saving Data

To save an SPSS data file, the Data Editor window must be the active window.

E From the menus choose:

File

Save

Browse to the desired directory.

Page 64

Chapter 3

TypeanameforthefileintheFilenametextbox. The Variable

s button can be used to select which variables in the Data Editor are

saved to the SPSS data file. By default, all variables in the Data Editor are retained.

E Click Save.

The name in the title bar of the Data Editor will change to the filename you specified. This confirms that the file has been successfully saved as an SPSS data file. The file contains bo

th variable information (names, type, and, if provided, labels and missing

value codes), and all data values.

Page 65

Chapter

Using the Dat

The Data Editor displays the contents of the active data file. The information in the Data Editor

 In Data Vie

(observations).

 In Variable View, each row is a variable, and each column is an attribute

associated with that variable.

Variables are used to represent the different types of data that you have compiled. A common ana equivalent to a variable. Variables come in many different types, including numbers, strings, currency, and dates.

Entering Numeric Data

Data can be entered into the Data Editor, which may be useful for small data files or for making minor edits to larger data files.

consists of variables and cases.

w, columns represent variables and rows represent cases

logy is that of a survey. The response to each question on a survey is

aEditor

E Click the Variable View tab at the bottom of the Data Editor window.

Define the needed: age, marital status,andincome.

variables that are going to be used. In this case, only three variables are

Page 66

Chapter 4

Figure 4-1

Variable names in Variable View

E In the first row of the first column, type age. E In the second row, type marital. E In the third row, type income.

New variables are automatically given a numeric data type. If you do

n’t enter variable names, unique names are automatically created. However,

these names are not descriptive and are not recommended for large data files.

E Click the Data View tab to continue entering the data.

The names that you entered in Variable View are now the headings for the first three columns i

nDataView.

Page 67

Begin entering data in the first row, starting at the first column.

Figure 4-2

Values enter

ed in Data View

Using the Data E

ditor

E In the a E In the E In the i E Move th E In the a E In the m E In the i

ge column, type

marital column, type

ncome column, type

55.

72000.

e cursor to the first column of the second row to add the next subject’s data.

ge column, type

arital column, type

ncome column, type

53.

153000.

Page 68

Chapter 4

Currently, the age and marital columns display decimal points, even though their values are intended to be integers. To hide the decimal points in these variables:

E Click the Variable View tab at the bottom of the Data Editor window. E Select the Decimals column in the age row and type 0 to hide the decimal. E Select the Decimals column in the marital row and type 0 to hide the decimal.

Figure 4-3

Updated decimal property for age and marital

Enteri

ng String Data

Non-nu

E Click t E In the f

meric data, such as strings of text, can also be entered into the Data Editor.

Variable View tab at the bottom of the Data Editor window.

irst cell of the first empty row, type

sex for the variable name.

Page 69

Using the Data E

Click the Type cell.

E Click the button in the Type cell to open the Variable Type dialog box.

Figure 4-4

Button shown

in Type cell for sex

ditor

E Selec

String to specify the variable type.

Page 70

Chapter 4

Click OK to save your changes and return to the Data Editor.

Defining

Figure 4-5

Varia ble Typ

Data

In additi

e dialog box

on to defining data types, you can also define descriptive variable and value labels for variable names and data values. These descriptive labels are used in statistical reports and charts.

Adding a Variable Label

Labels are meant to provide descriptions of variables. These descriptions are often longer versions of variable names. Labels can be up to 256 characters long. These labels a

re used in your output to identify the different variables.

E Click t E In the La E In the La E In the La

Variable View tab at the bottom of the Data Editor window.

bel column of the age row, type bel column of the marital row, type bel column of the income row, type

Respondent's Age.

Marital Status.

Household Income.

Page 71

In the Label column of the sex row, type Gender.

Figure 4-6

Varia ble lab

els entered in Variable View

Using the Data E

ditor

Changing Variable Type and Format

The Type column displays the current data type for each variable. The most common are num file, the income variable is defined as a numeric type.

E Click the Type cell for the income row, and then click the button to open the Variable

Type dialog box.

eric and string, but many other formats are supported. In the current data

Page 72

Chapter 4

Select Dollar intheVariableTypedialogbox.

Figure 4-7

Varia ble Typ

The formatting options for the currently selected data type are displayed.

E Select the format of this currency. For this example, select $###,###,###. E Click OK to save your changes.

Adding Val

Value labe the case of this example, there are two acceptable values for the marital variable. A value of 0 means that the subject is single, and a value of 1 means that he or she is mar

e dialog box

ue Labels for Numeric Variables

ls provide a method for mapping your variable values to a string label. In

ried.

E Click th

e Values cell for the marital row, and then click the button to open the Value

Labels dialog box. The value is the actual numeric value. The value l

E Type 0 in t E Type Sing

abel is the string label applied to the specified numeric value.

he Value field.

in the Value Label field.

Page 73

Using the Data E

Click Add to add this label to the list.

Figure 4-8

Value La bel s

E Repeat the process, this time typing 1 in the Value field and Married in the Value

dialog box

Label field.

E Click Add, and then click OK to save your changes and return to the Data Editor.

These labels can also be displayed in Data View, which can help to make your data more readable.

E Click the Data View tab at the bottom of the Data Editor window.

ditor

E From the menus choose:

View

Value Labels

The labels are now displayed in a list when you enter values in the Data Editor. This has the benefit of suggesting a valid response and providing a more descriptive answer.

Page 74

Chapter 4

Figure 4-9

Value labels displayed in Data View

Adding Value Labels for String Variables

String variables may require value labels as well. For example, your data may use

letters, M or F, to identify the sex of the subject. Value labels can be used to

single specify that M stands for Male and F stands for Female.

E Click the Variable View tab at the bottom of the Data Editor window. E Click the Values cell in the sex row,andthenclickthebuttontoopentheValue

Labels dialog box.

E Type F in the Value field, and then type Female in the Value Label field.

Page 75

Using the Data E

Click Add to add this label to your data file.

Figure 4-10

Value La bel s

E Repeat the process, this time typing M in the Value field and Male in the Value

dialog box

Label field.

E Click Add, and then click OK to save your changes and return to the Data Editor.

Because string values are case sensitive, you should make sure that you are consistent. Alowercasem is not the same as an uppercase M.

ditor

Using Value Labels for Data Entry

In a previous example, we chose to have value labels displayed rather than the actual data by selecting Value Labels from the View menu. You can use these values for data entry.

E Click the Data View tab at the bottom of the Data Editor window. E In the first row, select the cell for sex and select Male from the drop-down list.

Page 76

Chapter 4

In the second row, select the cell for sex and select Female from the drop-down list.

Figure 4-11

Using variab

Only de

le labels to select values

fined values are listed, which helps to ensure that the data entered are in a

format that you expect.

Handli

ng Missing Data

g or invalid data are generally too common to ignore. Survey respondents may

Missin refuse to answer certain questions, may not know the answer, or may answer in an unexpected format. If you don’t take steps to filter or identify these data, your

sis may not provide accurate results.

analy

For numeric data, empty data fields or fields containing invalid entries are handled

by converting the fields to system missing, which is identifiable by a single period.

Page 77

Figure 4-12

Missing values displayed as periods

Using the Data E

ditor

Missin

The reason a value is missing may be important to your analysis. For example, you may fin

ditusefultodistinguishbetweenthosewhorefusedtoansweraquestionand

those who didn’t answer a question because it was not applicable.

g Values for a Numeric Variable

Variable View tab at the bottom of the Data Editor window.

E Click E Click

the the Missing cell in the age row,andthenclickthebuttontoopentheMissing

Values dialog box.

Page 78

Chapter 4

In this dialog box, you can specify up to three distinct missing values, or a range of values plus one additional discrete value.

Figure 4-13

Missing Values dialog box

E Select Discrete missing values. E Type 999 in the first text box and leave the other two empty. E Click OK to save your changes and return to the Data Editor.

Now that the missing data value has been added, a label can be applied to that value.

E Click the Values cell in the age row,andthenclickthebuttontoopentheValue

Labels dialog box.

E Type 999 in the Value field. E Type No Response in the Value Label field.

Figure 4-14

Value Labels dialog box

Page 79

Click Add to add this label to your data file.

E Click OK to save your changes and return to the Data Editor.

Missing Valu

Missing val Unlike numeric values, empty fields in string variables are not designated as system missing. Rather, they are interpreted as an empty string.

E Click the Variable View tab at the bottom of the Data Editor window. E Click the Missing cell in the sex row,andthenclickthebuttontoopentheMissing

Values dial

E Select Dis E Type NR in t

Missing values for string variables are case sensitive. So, a value of nr is not treated as a missing value.

Using the Data E

es for a String Variable

ues for string variables are handled similarly to those for numeric values.

og box.

crete missing values

hefirsttextbox.

ditor

E Click OK to save your changes and return to the Data Editor.

Now you can add a label for the missing value.

E Click the Values cell in the sex row,andthenclickthebuttontoopentheValue

Labels dialo

E Type NR in th

gbox.

e Value field.

Page 80

Chapter 4

Type No Response in the Value Label field.

Figure 4-15

Value La bel s

E Click Add to add this label to your project. E Click OK to save your changes and return to the Data Editor.

dialog box

Copying and Pasting Value Attributes

Once you’ve defined variable attributes for a variable, you can copy these attributes and apply them to other variables.

Page 81

In Variable View, type agewed in the first cell of the first empty row.

Figure 4-16

agewed varia

bleinVariableView

Using the Data E

ditor

E In the E Click t E From th

E From the menus choose:

Label column, type he Values cell in the age row.

e menus choose:

Edit

Copy

Click the Values cell in the agewed row.

Edit

Paste

Age Married.

Page 82

Chapter 4

The defined values from the age variable are now applied to the agewed variable.

Figure 4-17

Values paste

dforagewed

Page 83

Using the Data E

ditor

To apply the attribute to multiple variables, simply select multiple target cells (click anddragdownthecolumn).

Figure 4-18

Multiple cells selected

Page 84

Chapter 4

When you paste the attribute, it is applied to all of the selected cells.

Figure 4-19

Values paste

dintomultiplecells

New variables are automatically created if you paste the values into empty rows.

You can also copy all of the attributes from one variable to another.

Page 85

Click the row number in the marital row.

Figure 4-20

Selected row

Using the Data E

ditor

E From th

Edit

Click the row number of the first empty row.

E From the menus choose:

Edit

e menus choose:

Copy

Paste

Page 86

Chapter 4

All of the attributes of the marital variable are applied to the new variable.

Figure 4-21

Values paste

dintorow

Defining Variable Properties for Categorical Variables

For categorical (nominal, ordinal) data, Define Variable Properties can help you

value labels and other variable properties. Define Variable Properties:

define

 Scans

 Identifies unlabeled values and provides an “auto-label” feature.  Provides the ability to copy defined value labels from another variable to the

the actual data values and lists all unique data values for each selected

variable.

selected variable or from the selected variable to multiple additional variables.

Page 87

Using the Data E

ditor

This example uses the data file demo.sav. This data file already has defined value labels; so before we start, let’s enter a value for which there is no defined value label:

E InDataViewoftheDataEditor,clickthefirstdatacellforthevariableownpc (you

may have to sc

E From the men

Data

Define Variable Properties...

Figure 4-22

Initial Defi

roll to the right) and enter the value

us choose:

ne Variable Properties dialog box

99.

In the initial Define Variable Properties dialog box, you select the nominal or ordinal variables for which you want to define value labels and/or other properties.

Since Define Variable Properties relies on actual values in the data file to help you

make good choices, it needs to read the data file first. This can take some time if your data file contains a very large number of cases, so this dialog box also allows you to limit the number of cases to read, or scan. Limiting the number of cases is not

Page 88

Chapter 4

necessary for our sample data file. Even though it contains over 6,000 cases, it doesn’t take very long to scan that many cases.

E Drag and drop Owns computer [ownpc] through Owns VCR [ownvcr] into the

Variables t

oScanlist.

You might notice that the measurement level icons for all of the selected variables indicate that they are scale variables, not categorical variables. By default, all numeric variables a

re assigned the scale measurement level, even if the numeric values are actually just codes that represent categories. All of the selected variables in this example are really categorical variables that use the numeric values 0 and 1 to stand for No and Y

es, respectively—and one of the variable properties that we’ll change

with Define Variable Properties is the measurement level.

E Click Continue.

Figure 4-2

Define Var

E In the Scanned Variable List, select ownpc.

iable Properties main dialog box

Page 89

Using the Data E

The current level of measurement for the selected variable is scale. You can change the measurement level by selecting one from the drop-down list or you can let Define Variable Pr

E Click Sugge

Figure 4-24

Suggest Measurement Level dialog box

operties suggest a measurement level.

ditor

Since the variable doesn’t havevery many different values and all of the scanned cases

n integer values, the proper measurement level is probably ordinal or nominal.

contai

E Select

Ordinal and then click Continue.

The measurement level for the selected variable is now ordinal. The Value Labels Grid displays all of the unique data values for the selected variable,

any defi

ned value labels for these values, and the number of times (count) each

value occurs in the scanned cases.

Page 90

Chapter 4

The value that we entered, 99, is displayed in the grid. The count is only 1 because we changed the value for only one case, and the Label column is empty because we haven’t def

ined a value label for 99 yet. An

X in the first column of the Scanned

Variable List also indicates that the selected variable has at least one observed value without a defined value label.

E In the Label columnforthevalueof99,enterNo answer. E Then click (check) the box in the Missing column. This identifies the value 99 as user

missing.Da

ta values specified as user missing are flagged for special treatment and

are excluded from most calculations.

Figure 4-25

New variabl

e properties defined for ownpc

Before we complete the job of modifying the variable properties for ownpc,let’s

he same measurement level, value labels, and missing values definitions to

apply t the other variables in the list.

E In the Copy Properties group, click To Other Variables.

Page 91

Figure 4-26

Apply Labels and Level dialog box

In the Ap then click

ply Labels and Level dialog box, select all of the variables in the list, and

Copy.

Using the Data E

ditor

Page 92

Chapter 4

If you select any other variable in the list in the Define Variable Properties main dialog box now, you’ll see that they are all now ordinal variables, with a value of 99 defined as u

Figure 4-27

New variable properties defined for ownfax

ser missing and a value label of No answer.

E Click OK to save all of the variable properties that you have defined.

Page 93

Chapter

Examining S u

mmary Statistics

for Individual Variables

This chapt of a variable influences the types of statistics that should be used. We will use the data file demo.sav.

Level of Measurement

Different summary measures are appropriate for different types of data, depending on the level of measurement:

Categoric

gender or marital status). Also referred to as qualitative data. Categorical variables can be string (alphanumeric) data or numeric variables that use numeric codes to represen basic types of categorical data:

 Nominal. Categorical data where there is no inherent order to the categories. For

 Ordinal. Categorical data where there is a meaningful order of categories, but

er discusses simple summary measures and how the level of measurement

al.

Data with a limited number of distinct values or categories (for example,

t categories (for example, 0 = U nmarried and 1 = Married). There are two

example, “marketing” or “research.”

there isn’t a measurable distance between categories. For example, there is an order t values can’t be calculated.

a job category of “sales” isn’t higher or lower than a job category of

o the values high, medium, and low, but the “distance” between the

Page 94

Chapter 5

Scale. Data measured on an interval or ratio scale, where the data values indicate

both the order of values and the distance between values. For example, a salary of $72,195 is h

igher than a salary of $52,398, and the distance between the two values is

$19,797. Also referred to as quantitative or continuous data.

Summary Mea

For categor of cases in each category. The mode is the category with the greatest number of cases. For ordinal data, the median (the value above and below which half the cases fall) mayalsobe

The Frequencies procedure produces frequency tables that display both the number and percentage of cases for each observed value of a variable.

E From the menus choose:

Analyze

Descripti

Frequenci

Select Ow

list.

Figure 5-1

Categoric

sures f or Categorical Data

ical data, the most typical summary measure is the number or percentage

a useful summary measure if there is a large number of categories.

ve Statistics

es...

ns PDA (ownpda) and Owns TV (owntv) and move them into the Variable(s)

al variables selected for analysis

E Click OK to run the procedure.

Page 95

Figure 5-2

Frequency tables

Examining Summ

ary Statistics for Individual Variables

The frequency tables are displayed in theViewerwindow.Thefrequencytables reveal that only about 21% of the people own PDAs, but almost everybody owns a TV (99.2%). This might not be an interesting revelation, although it might be interesting to find out more about the small group of people who do not own televisions.

Charts for Categorical Data

You can graphically display the information in a frequency table with a bar chart or pie chart.

E Open the Frequencies dialog box again. (The two variables should still be selected.)

Page 96

Chapter 5

You can use the Dialog Recall button on the toolbar to quickly return to recently used procedures.

Figure 5-3

Dialog Recall tool

E Click Char E Select Bar

Figure 5-4

Frequencies Charts dialog box

andthenclickContinue.

charts

E Click OK in the main dialog box to run the procedure.

Page 97

Figure 5-5

Bar chart

Examining Summ

ary Statistics for Individual Variables

Summar

E Open

In addition to the frequency tables, the same information is now displayed in the form of bar c

harts, making it easy to see that most people do not own PDAs but almost

everyone owns a TV.

y Measures for Scale Variables

are many summary measures available for scale variables, including:

There

 Meas

ures of central tendency.

are the mean (arithmetic average) and median (value above and below which half the cases fall).

 Measures of dispersion. Statistics that measure the amount of variation or spread

data include the standard deviation, minimum, and maximum.

in the

the Frequencies dialog box again.

The most common measures of central tendency

Page 98

Chapter 5

Click Reset to clear any previous settings.

E Select Household income in thousands (income) and move it into the Variable(s) list.

Figure 5-6

Scale variab

E Click Statistics. E Select Mean, Median, Std. deviation, Minimum,andMaximum.

Figure 5-7

Frequencies Statistics dialog box

le selected for analysis

E Click Continue.

Page 99

Examining Summ

Deselect Displayfrequency tablesin the main dialog box. (Frequency tables are usually

ary Statistics for Individual Variables

not useful for scale variables since there may be almost as many distinct values as there are ca

E Click OK to

The Frequenc

Figure 5-8

Frequencies Statistics table

ses in the data file.)

run the procedure.

ies Statistics table is displayed in the Viewer window.

In this example, there is a large difference between the mean and the median, with the mean bei

ng more than 25,000 greater than the median. This indicates that the values

are not normally distributed. We can visually check the distribution with a histogram.

Page 100

Chapter 5

Histograms for Scale Variables

E Open the Frequencies dialog box again. E Click Charts. E Select Histograms and With normal curve.

Figure 5-9

Frequencies

E Click Continue and click OK in the main dialog box to run the procedure.

Charts dialog box