3036-Prelims.qxd 10/19/02 10:19 AM Page i Interpreting Quantitative Data with SPSS 3036-Prelims.qxd 10/19/02 10:19 AM Page ii 3036-Prelims.qxd 10/19/02 10:19 AM Page iii Interpreting Quantitative Data with SPSS Rachad Antonius SAGE Publications London • Thousand Oaks • New Delhi 3036-Prelims.qxd 10/19/02 10:19 AM Page iv © Rachad Antonius 2003 First published 2003 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act, 1988, this publication may be reproduced, stored or transmitted in any form, or by any means, only with the prior permission in writing of the publishers, or in the case of reprographic reproduction, in accordance with the terms of licences issued by the Copyright Licensing Agency Inquiries concerning reproduction outside those terms should be sent to the publishers SAGE Publications Ltd Bonhill Street London EC2A 4PU SAGE Publications Inc 2455 Teller Road Thousand Oaks, California 91320 SAGE Publications India Pvt Ltd 32, M-Block Market Greater Kailash - I New Delhi 110 048 British Library Cataloguing in Publication data A catalogue record for this book is available from the British Library ISBN 7619 7398 ISBN 7619 7399 (pbk) Library of Congress Control Number: 2002 102 782 Typeset by C&M Digital (P) Ltd., Chennai, India Printed in Great Britain by TJ International Ltd, Padstow, Cornwall 3036-Prelims.qxd 10/19/02 10:19 AM Page v CONTENTS ACKNOWLEDGMENTS ix FOREWORD TO THE STUDENT xi FOREWORD TO THE INSTRUCTOR THE BASIC LANGUAGE OF STATISTICS Introduction: Social Sciences and Quantitative Methods Data Files The Discipline of Statistics Populations, Samples, and Units Descriptive Statistics Inferential Statistics Variables and Measurement Importance of the Level of Measurement Concepts, Dimensions, and Indicators Summary Keywords Suggestions for Further Reading Exercises THE RESEARCH PROCESS Main Steps in Social Research Summary Keywords Suggestions for Further Reading Exercises UNIVARIATE DESCRIPTIVE STATISTICS Measures of Central Tendency Measures of Dispersion Measures of Position Other Measures Graphical Representation of the Distribution of Data The General Shape of a Distribution Methodological Issues Summary Keywords Suggestions for Further Reading Exercises xvii 1 9 10 16 17 18 19 19 20 22 23 31 31 31 33 34 36 46 51 52 53 66 67 69 70 71 71 3036-Prelims.qxd 10/19/02 10:19 AM Page vi vi CONTENTS WRITING A DESCRIPTIVE SUMMARY How to Write a Descriptive Report Summary Keywords Suggestions for Further Reading Exercises NORMAL DISTRIBUTIONS Properties of Normal Distributions Using the Table of Areas Under the Normal Curve Numerical Examples Summary Keywords Suggestions for Further Reading Exercises SAMPLING DESIGNS Types of Samples Errors of Measurement Summary Keywords Suggestions for Further Reading Exercises DATABASES ON SOCIAL STATISTICS Illustration of a Data Search on Selected Sites Printed Reports of Statistics Canada (or StatCan) CD-ROMs and Disks Online Data at StatCan Keywords Suggestions for Further Reading Exercises STATISTICAL ASSOCIATION The Case of Two Quantitative Variables The Case of Two Qualitative Variables The Case of One Quantitative and One Qualitative Variable Ordinal Variables Statistical Association as a Qualitative Relationship Summary and Conclusions Keywords Suggestions for Further Reading Exercises INFERENTIAL STATISTICS: ESTIMATION Inferential Statistics The Logic of Estimation: Proportions and Percentages Estimation of a Percentage: The Calculations Estimation of a Mean Estimation of a Mean: The Calculations Effect of the Sample Size on the Margin of Error Calculation of the Sample Size Needed in a Survey Summary and Conclusions 78 78 95 96 96 96 97 98 100 103 105 106 106 106 107 108 117 118 119 119 119 122 126 131 135 136 140 140 140 142 145 148 153 153 154 156 158 158 158 161 161 163 165 168 169 170 171 172 3036-Prelims.qxd 10/19/02 10:19 AM Page vii CONTENTS vii Keywords Suggestions for Further Reading Exercises 10 INFERENTIAL STATISTICS: HYPOTHESIS TESTING 173 173 174 177 Sampling Distributions The Logic of Hypothesis Testing The Detailed Procedure for Hypothesis Testing Understanding the Probabilities of Error The Various Forms of the Alternative Hypothesis Hypothesis Testing When σ is Unknown Hypothesis Testing with Two Independent Samples Hypothesis Testing in Statistical Software t-Tests Summary and Conclusions Keywords Suggestions for Further Reading Exercises 179 180 182 184 185 188 189 190 190 191 191 192 192 SYNTHESIS: ANALYZING A TOPIC IN A DATA FILE 195 The Data File Itself The Topic and the Questions The Analysis 195 195 196 REVIEW QUESTIONS 202 LAB LAB LAB LAB LAB LAB LAB LAB LAB LAB LAB 206 213 216 226 235 239 242 245 248 256 1: 2: 3: 4: 5: 6: 7: 8: 9: 10: 11: LAB 12: LAB 13: LAB 14: GETTING STARTED WITH SPSS WORKING WITH A WORD PROCESSOR EXPLORING DESCRIPTIVE STATISTICS RECODING; THE HELP MENU CHARTS IN SPSS MORE ON DESCRIPTIVE STATISTICS RANDOM SAMPLING ACCESSING DATABASES ON THE INTERNET CREATING A DATA FILE CROSS-TABULATIONS (TWO-WAY TABLES) COMPARING THE MEANS OF VARIOUS SUBGROUPS CORRELATION AND REGRESSION CONFIDENCE INTERVALS t-TESTS 261 266 272 277 APPENDIX AREAS UNDER THE NORMAL CURVE 284 APPENDIX TABLE OF RANDOM NUMBERS 285 GLOSSARY OF STATISTICAL TERMS 286 GENERAL BIBLIOGRAPHY 296 INDEX 299 3036-Prelims.qxd 10/19/02 10:19 AM Page viii 3036-Prelims.qxd 10/19/02 10:19 AM Page ix ACKNOWLEDGMENTS A number of contingencies have presided over the coming about of this book … and a number of people have played a role in its birth I would like to acknowledge their input here First of all, there was Louise Corriveau, who first encouraged me to work on a manual of quantitative methodology for the social sciences She introduced me to a statistician, the late Robert Trudel, and together we wrote Méthodes quantitatives appliquées aux sciences humaines Our long and elaborated discussions on every aspect of the book, both from the point of view of statistics and from the point of view of pedagogy, helped shape my views of how that subject matter ought to be taught I should point out the role played then by Mr Charles Dufresne, whose advice on the form, content and organization of that book was an extremely formative experience As computers were becoming available for our classes, we started using software packages to teach this course After experimenting with several packages, the administration and instructors of the course opted for SPSS We had manuals to teach SPSS, but we did not have a manual to teach quantitative methods for the social sciences with the help of a package such as SPSS I thus wrote a series of class notes in quantitative methodology using SPSS The focus was on methodology, and SPSS was a tool, not an end in itself With the comments of my students and my colleagues at Champlain College – St-Lambert, these notes gradually evolved into an experimental manuscript This book is the result of these efforts I would like to thank my colleagues – both in the Mathematics department and in the Methodology module – for letting me teach the course, and for testing the manual in their classes The administration at Champlain was quite supportive, and accommodated my needs in terms of teaching and of granting (unpaid …) leaves of absence when that was required They also provided numerous signs of encouragement and appreciation of this work As any author knows, writing a book puts a lot of stress on the daily organization of family life I would like to thank my spouse, Y.G., and my children, Marc and Gabriel, for putting up with my constant preoccupation with statistics and methodology during moments when I should have been available to interact with them Finally, I would like to thank all the staff at SAGE and Keyword Publishing Services for their professional editing job Rachad Antonius Montreal, May 20, 2002 3036-Ref.qxd 10/19/02 10:23 AM Page 298 3036-Index.qxd 10/19/02 10:21 AM Page 299 INDEX Page references relating to figures and tables only are given in italics and bold, respectively α, significance level, 182, 185, 294 abilities to be acquired, xii–xiii acceptance or rejection regions, null hypothesis, 182, 191, 286, 287 aging data, 130 alternative (research) hypothesis, 23, 179, 185–8, 286 analysis, comprehensive, 241 analytical reports see reports answers, valid and missing, 79–80, 220–1 archival research, 28–9, 108 see also statistics, official area under curve normal distribution, 100–3, 186 z-values, 283–4 ASCII data 123 association, statistical, 142–60 cross-tabulation, 197–8 definition, 156–7, 256 ordinal level, 200 for quantitative and qualitative variables, 153, 154–6, 199 and relationship, 154 strength, 144 average see mean β, significance level, 185, 294 bar charts, 53–58, 70, 197, 199 clustered, 55–6, 63, 256 and histograms, 62–3 simple, 53–5 in SPSS, 219, 222, 235 stacked, 57 bell-shaped curve, normal distribution, 66, 97, 286, 290 bias, 27, 114, 118 box plots clustered, 238 quantitative variables, 63–4 in SPSS, 68, 237–8 Canada census data, 137–8 see also Statistics Canada case, 286 see also unit categories, 69 appropriate measures and charts, 81 definition, 68 exhaustive, 12 mutually exclusive, 12 cause, 152, 157 CD-ROMS and disks, 124, 135–6 cell, 149 frequency, 286 census, 26, 286 data, 108, 131, 137, 247 see also statistics, official central tendency measures, 35, 36–46, 69 qualitative variables, 36–8 quantitative variables, 38, 198 charts see bar charts; graphical representation classes, 15–16 interval, 286 limits, 59, 286 mark, 286 midpoint, 59 cluster, sample, 112 codebook, 3, 26, 210, 215, 226, 286 coded variables, mean, 40–2, 198, 240 codes and coding, 4, 6, 14, 198 see also recoding coefficient of variation, 50–1, 294 Compare Means procedure, SPSS, 198, 199, 200 3036-Index.qxd 10/19/02 10:21 AM 300 Page 300 I N T E R P R E T I N G Q U A N T I TAT I V E D ATA W I T H S P S S computerized data file see data file conditions, suitable, 36 confidence interval definition, 286 graphical representation, 274 proportion or percentage, 275–6 in SPSS, 272–6, 282 confidence level, 163, 167, 168, 170, 173 confidence statement, 163, 173, 198, 199, 200–1 confidentiality, 30 consent, informed, 30 contingency table see cross-tabulation continuous scales, 16 control group, 27–8 convenience samples, 116 Copy command, 80 CopyObject command, 80 correlation, 147–8, 200, 287, 290, 291 coefficient (r) 148, 149, 199, 271, 287 and regression, 266–71 spurious, 293 criminal justice data, 130 critical region see acceptance or rejection regions critical value see cut-off point cross-tabs procedure, SPSS, 200 cross-tabulation, 150, 197–8, 200, 256–60, 287 CSV file format, 123, 287 cumulative distribution, 287 cut-off point, 182, 186, 187, 188, 191 data aggregate, 29, 123 analysis, 27, 29–30 collection, 27, 29, 107 definition, 2, 287 entry, 27, 29 generalizing from sample to population, 107, 161 grouped, 39–40, 55, 58, 198–9 interpretation, 22 organization, 27 presentation, 27 primary and secondary, 122, 291, 292 raw, 131–2, 292 reduction, 287 sets, 123 see also qualitative data; quantitative data data file, 2–6 analysis, 195–201 creation, 248–55 definition, 2, 287 description, 80, 195 electronic, xii, 2–3, 27, 248 formats, 123–4 Data View, SPSS, databases Internet, 245–7 social statistics, 122–41 deciles, 35, 51, 69 density curve, 62 dependent and independent variables, 144 in cross-tabulations, 259 Explore command, 261 dependent variables definition, 287–8 nominal, 197–8 ordinal, 199–201 ratio/interval scale, 198–9 descriptive reports see reports descriptive statistics see statistics, descriptive deviation from the mean, 48, 288 mean, 289 diagrams see graphical representation dichotomy, 288 digit, definition, 110 dimensions, and indicators, 17, 18 discrete scales, 16 dispersion, measures, 35, 46–51, 69, 288 distribution definition, 288 graphical representation, 53–65, 70 shape, 35, 65–7 symmetry/skewness, 35, 46, 66–7, 294 tails, 186 see also normal distribution double-blind experiment, 28 E-Stat disk, 135–6 education data, 130 electronic data file see data file element see unit error probabilities, 162, 172–3, 184–5 in confidence statement, 163, 170 errors measurement, 117–18 observation, 117 3036-Index.qxd 10/19/02 10:21 AM Page 301 INDEX errors, cont prediction, 144 random, 118 sampling, 118 systematic, 294 Types I and II, 184–5, 191, 281, 294 see also margin of error estimate, definition, 288 estimation, 163–5, 171 inferential statistics, 161–76 mean, 163, 164, 168–70 percentage, 165–8 ethical questions, 30 experimental research, 108 experiments, 27, 28 design, 28, 288 explanatory variable, 155, 157 five-number summary, 63 freedom to withdraw from research project, 30 frequency, 35, 36 definition, 288 distribution, 289 expected (theoretical), 288 observed, 149, 290 quantitative, ungrouped variable, 227 relative, 199 frequency polygon, 62 frequency table, 221 analysis, 87–91 census data, 131–2 in SPSS, 211 graphical representation appropriate, 81 confidence intervals, 274 distribution, 53–5, 70 importance, xxi–xxii nominal variables, 197 quantitative variable, 198 in SPSS, 79 grouped variables see data, grouped GSS Directory, 128–31 health and medical care data, 130 histograms, 70, 198 and bar charts, 62–3 drawing manually, 60–2 quantitative data, 58–63 in SPSS, 59, 219, 236–7 301 HTML file format, 247 hypothesis definition, 289 see also alternative (research) hypothesis; null hypothesis hypothesis testing, 177–94, 289, 294 logic, 180–2 procedure, 182–4 in SPSS, 278–82 statistical software, 190 two independent samples, 189–90 when standard distribution is unknown, 188–9 independent samples, t-test, 279–82 index, StatCan catalog, 131 indicators, and dimensions, 17, 18 inferential statistics see statistics, inferential information sources, Internet, 25 intellectual maturity, xxii–xxiii Inter-university Consortium for Political and Social Research (ICPSR), 125, 128–31 International Association for Statistical Computing, 125 international organizations, 123, 124–5, 246 Internet databases, 245–7 information sources, 25 statistical archives, 29 Internet for Social Statistics, 128 interquartile range, 48, 69 interval estimate, 168, 170 interval scales, 15 intuition, developing, xxi–xxii judgment samples, 116 keyword search, 126, 131 kurtosis, 35, 67, 68, 69, 289 label, variable see variable label level of confidence see confidence level level of significance see significance level Likert scale, 13–14 limits, class, 59 line charts, 64–5 literature review, 24, 25 3036-Index.qxd 10/19/02 10:21 AM 302 Page 302 I N T E R P R E T I N G Q U A N T I TAT I V E D ATA W I T H S P S S majority, 37 margin of error, 161–2, 172, 199 calculation, 166, 168, 199 in confidence statement, 163, 169–70 and sample size, 170–1 matched-pair design, 28 mean coded variables, 40–2, 198, 240 comparing, 261–5 in confidence statement, 169–70 definition, 38, 289 estimation, 168–70 grouped data, 39–40 and median, 45–6, 69–70, 198 sampling distribution, 180 trimmed, 39 weighted, 42–4, 69, 113, 294 when to use, 69 measurement errors, 117–18 level, 11–12, 16–17, 36, 69, 70, , 81, 210, 252 and variables, 10–16 measures, appropriate, 80, 81 median definition, 44–5, 289 and mean, 45–6, 69–70, 198 when to use, 46, 69 midpoint, class, 59 missing values in SPSS, 210, 250–2 see also answers, valid and missing modal category, 37 modal class, 289 mode, 45, 62, 69, 198, 290 nominal variables appropriate measures and charts, 81 association, 148–53 dependent, 197–8 examples, 12, 13 graphical representation, 197 grouped, 199 mean not appropriate, 52 non-probabilistic samples, 114–17 non-proportional stratified random samples, 113 normal distribution, 97–106, 290 area under the curve, 100–3, 186 bell-shaped curve, 66, 97, 286, 290 and margin of error, 166–7 normal distribution, cont properties, 98–100 and randomness, 98, 103 sampling distribution, 180 standard, 99 null hypothesis, 177–9, 290 acceptance or rejection, 182, 184–5 numeric variables, 12, 249–50 appropriate measures and charts, 81 quantitative, 14, 15, 17 objectivity and subjectivity, observation, errors, 117 observations, recording, 11 official statistics see statistics, official one-sample t-test, 277–9 one-tailed tests, 186, 187–8, 290 online data, Statistics Canada, 136–40 online databases, 124, 125 open class, 290 operationalization, 17–18, 25 ordering, ranking, 12 ordinal variables, 12, 13 appropriate measures and charts, 81 association, 153–4, 200 dependent variable, 199–201 qualitative and quantitative, 14, 17 outliers, 68, 290 output, meaningless, 27, 35–6, 79, 148, 239 parameters, 107, 163, 290 Pearson product-moment correlation coefficient, 148, 267 see also correlation pedagogical approach, xix–xx percentages, 36, 52, 53, 69, 167 column and row, 152, 259 confidence intervals, 275–6 in confidence statement, 163 estimation, 165–8 total and valid, 197 percentiles, 35, 51, 69, 290 pie charts, 58, 70, 197, 199, 291 in SPSS, 219, 236 placebo, 28 plurality, 37 point estimate, 164, 168, 170, 291 polarization, 79, 87, 90 population in confidence statement, 163, 168 3036-Index.qxd 10/19/02 10:21 AM Page 303 INDEX population, cont definition, 7, 291 mean, 38 pyramid, 61–2, 70 and sample, size, 291, 293 standard deviation, 49, 190 standard distribution, 189 position, measures, 35, 51, 69 precision, 161 prediction, 144, 145–7 printing output, 210, 215 probability of error see error probabilities probability sample, 108–13, 291 problematique, 23 proofreading, 80 proportional stratified random samples, 113 proportions, 35, 52, 53, 69, 167 confidence intervals, 275–6 estimation, 171 publications statistical, 124 Statistics Canada, 132–6 qualitative data, graphical representation, 70 qualitative variables association, 148–53 measures of central tendency, 36–8 measures of dispersion, 46–7 quantification, 1–2 quantitative data graphical representation, 70 histograms, 58–63 from research, 108 quantitative methods definition, 2, 291 questions arising, in social science, xviii, 1–2 quantitative variables association, 145–8, 153 box plots, 63–4 central tendency, 38, 198 dispersion, 47–51 graphical representation, 198 grouped, 55 normal distribution, 98, 103 numeric, 14, 15, 17 ordinal, 17 SPSS Descriptives command, 222 ungrouped, 227 303 quartiles, 35, 48, 51, 69, 291 questionnaire, 26, 27, 291 Quick Data Links, 128, 130 quota sampling, 114–15, 291 r see correlation coefficient random error, 118 random numbers definition, 291 seed, in SPSS, 242 tables, 109–11, 285 random sample, 291–2 selection, 242–4 simple, 109–11 in SPSS, 242–4 randomness, and normal distribution, 98, 103 range, 47–8, 55, 69, 292 trimmed, 48 ranking, 12, 153 ratio, 35, 52–3, 69 between groups, 91 ratio/interval scale, 15, 198–9 recoding, 240–1 in SPSS, 226–34 regression and correlation, 266–71 line, 145, 292 relationship and association, 154 of authority, 30 spurious, 155–6 relevance, and truth, xx–xxi replacement sampling, 292 reports analytical, 87–95, 123 descriptive, xiii, 78–96, 123, 201 examples, 81–6, 91–5 presentation, 80 printed, 124 Statistics Canada, 131–40 writing, 241 representative sample, 292 research design, xii, 26, 108 effects and repercussions, 31 general question, 23–4 hypothesis see alternative (research) hypothesis process, 32 3036-Index.qxd 10/19/02 10:21 AM 304 Page 304 I N T E R P R E T I N G Q U A N T I TAT I V E D ATA W I T H S P S S research, cont qualitative aspects, xii question, 195–6 results, interpreting, 30 risk level, 162 sample/sampling cluster, 112 in confidence statement, 163 convenience, 116 definition, 7, 292 design, 27, 107–21, 292 distribution, 167, 179–80, 292 errors, 118 frame, 108, 110, 292 independent, 189–90 judgment, 116 mean, 38 non-probabilistic, 114–17 and population, quota, 114–15 replacement, 292 representative, 9, 108, 292 size, 27, 110, 170–2, 292 standard deviation, 50 stratified random, 113 subgroups, 261 systematic, 112 types, 108–12 volunteer, 116–17 see also random sample SAS see statistical software scaling, 292 scatter plot, 143, 199, 292 in SPSS, 268–70 search engines, 125 keyword, 126, 131 online databases, 125 secondary data analysis, 108 significance level, 277, 280, 282, 289 α, 182, 185 β, 185 significance test, 294 skewness see distribution, symmetry/skewness social research observing phenomena, 17 procedures, 22–3 quantitative methods, xii–xiii, xviii, 1–2 social statistics, databases, 122–41 SPSS Analyze, Descriptive Statistics, 216, 217 bar charts, 219 box plots, 68 card, for downloading data files, 124, 129 charts, 53, 79, 216, 219, 233–4, 235–8, 274 classroom use, xix Compare Means, 198, 199, 200, 261, 262–4 confidence intervals, 272–6, 282 Copy command, 80, 214–15 copying into Word document, 214 CopyObject command, 80, 214–15 correlation coefficient, 148 Crosstabs, 199, 200, 216, 256–60 Data Editor, 208, 248–9 Data View, 3, 4, 208, 209, 254 Descriptives command, 216, 222 difficulties, 239–41 electronic data file, 2–3 Explore command, 199, 216, 223–5, 261, 272 File Info, 210, 215, 226, 252–4 Frequencies command, 216, 217–21 frequency table, 211 getting started, 206–12 Help menu, 231–4 histograms, 59, 219 hypothesis testing, 278–82 interpreting output, 220–1 lab sessions, xiv matrix, 248, 252–4 meaningless/unwanted output, 79, 148, 216, 239 measurement level, 210, 252 Missing values, 210, 250–2 Mode, 218 new data file, 248 Output window, 214, 226 pie charts, 219 printing output, 210 random number seed, 242 random sampling, 109, 111, 242–4 Ratio command, 199, 216 Recode command, 227–31 recoding, 226–34 scatter plot, 268–70 Statistics menu, 261 Summarize sub-menu, 197 3036-Index.qxd 10/19/02 10:21 AM Page 305 INDEX SPSS, cont syntax, xvii, 211–12 Type, 210 using, xiii Utilities menu, Value Labels, 5, 209, 254 Variables, 3, 4, 5, 208, 209 View menu, standard deviation, 9, 46, 48–50, 69, 293 population 49, 190 sample, 50 standard distribution, population, 189 standard error, 167, 180, 293 standard normal distribution, 99 standard score, 293 statistic, definition, 107, 293 statistical association see association, statistical statistical inference, 293 statistical publications, 124 statistical software, 29 downloading data files, 124, 129 hypothesis testing, 190 meaningless output, 27, 35–6 statistics definition, 6–7, 293 descriptive, 9, 34, 67–68, 216–25, 288 inferential, 9–10, 161–76, 177–94 official, 122, 124, 245–7 see also Statistics Canada Statistics Canada CD-ROMs and disks, 135–6 online data, 136–40 publications, 132–6 reports, 94–5, 131–40 website, 245, 246–7 stratified random sampling, 113, 293 string variable, 249 Student’s t-distribution see t-distribution study tips, xiv–xv subjects, 27 substance abuse/mental health data, 130 summary in descriptive report, 201 statistical, 34 writing, 78–96 survey design, 26, 294 research, 108 305 survey, cont sample size required, 171–2 syntax file, 124 systematic sample, 112 t-distribution, 189, 294 t-tests, 190, 277–82, 294 independent samples, 279–82 one-sample, 277–9 tables, simple, 123 tendency, 144, 256 test statistic, 294 theoretical framework, 25 thesaurus, 126 thinking, inductive and deductive, xx totals, grand and marginal, 150 treatment effect, 294 group, 27 trend, 145 truth, and relevance, xx–xxi two-tailed test, 186, 188 two-way table see cross-tabulation Type I and Type II errors, 184–5, 191, 281, 294 unimodal, 294 unit, 7, 110 United Nations institutions, 123, 124–5, 246 Statistics Division, 126–8 univariate and bivariate analysis, 196–7 univariate measures, definition, 35 valid percent, 36 validity, 294 Value Labels, 3, 4, 294 values, variables, 11 variables comparing effect, 264–5 in confidence statement, 163, 168 definition, 10, 294 dependent and independent, 144, 195–6 description, 80 explanatory, 155, 157 label, 3, 4, 294 and measurement, 10–16 name, qualitative and quantitative, 11 recoded, 80 3036-Index.qxd 10/19/02 10:21 AM 306 variables, cont types, 10–11 values, 11 variance, 50, 69, 294 variation, 294 coefficient, 50–1, 294 measures, 294 ratio, 46–7 Page 306 I N T E R P R E T I N G Q U A N T I TAT I V E D ATA W I T H S P S S volunteer samples, 116–17 word-processing software, xiii, 213–15 Y-axis, truncation, 54–66, 70 z-values (z-scores), 99, 100, 105, 283–4, 294 3036-Index.qxd 10/19/02 10:21 AM Page 307 3036-Index.qxd 10/19/02 10:21 AM Page 308 3036-Index.qxd 10/19/02 10:21 AM Page 309 3036-Index.qxd 10/19/02 10:21 AM Page 310 3036-Index.qxd 10/19/02 10:21 AM Page 311 3036-Index.qxd 10/19/02 10:21 AM Page 312 ... Thanks are extended to SPSS Inc for permission to use copies of SPSS for Windows screens SPSS is a registered trademark of SPSS Inc For information about SPSS contact: SPSS Inc., 233 S Wacker... explained with some degree of detail SPSS is taught here not as an end in itself, and the SPSS labs should not be thought of as reference material for SPSS Rather, the SPSS labs were written in such... exercises that use the SPSS software After studying the theoretical material and doing the SPSS exercises, students should be able to collect their own data, enter it in SPSS, analyze it, interpret