Discovering statistics using IBM SPSS statistics:
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Melbourne
SAGE
[2018]
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| Edition: | 5th edition |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverzeichnis Seite 1043-1055 |
| Physical Description: | xxix, 1070 Seiten Illustrationen, Diagramme |
| ISBN: | 9781526419514 9781526445766 1526419513 9781526419521 9781526436566 |
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| 100 | 1 | |a Field, Andy |d 1973- |0 (DE-588)128714581 |4 aut | |
| 240 | 1 | 0 | |a Discovering statistics using SPSS |
| 245 | 1 | 0 | |a Discovering statistics using IBM SPSS statistics |c Andy Field |
| 250 | |a 5th edition | ||
| 264 | 1 | |a Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Melbourne |b SAGE |c [2018] | |
| 264 | 4 | |c © 2018 | |
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| 650 | 7 | |a learning |2 cabt | |
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| 650 | 7 | |a statistical analysis |2 cabt | |
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| adam_text | EXTENDED CONTENTS
PREFACE xv
HOW TO USE THIS BOOK xxi
THANK YOU xxv
SYMBOLS USED IN THIS BOOK xxix
SOME MATHS REVISION xxxi
1 WHY IS MY EVIL LECTURER FORCING ME TO LEARN STATISTICS? 1
1.1 What will this chapter tell me? 2
1.2 What the hell am I doing here? I don’t belong here 3
1.3 The research process 3
1.4 Initial observation: finding something that needs explaining 4
1.5 Generating and testing theories and hypotheses 5
1.6 Collecting data: measurement 9
1.7 Collecting data: research design 16
1.8 Analysing data 22
1.9 Reporting data 40
1.10 Brian’s attempt to woo Jane 44
1.11 What next? 44
1.12 Key terms that I’ve discovered 44
Smart Alex’s tasks 45
2 THE SPINE OF STATISTICS 47
2.1 What will this chapter tell me? 48
2.2 What is the SPINE of statistics? 49
2.3 Statistical models 49
2.4 Populations and samples 53
2.5 P is for parameters 54
2.6 E is for estimating parameters 60
2.7 S is for standard error 61
2.8 I is for (confidence) interval 64
2.9 N is for null hypothesis significance testing 72
2.10 Reporting significance tests 90
2.11 Brian’s attempt to woo Jane 92
2.12 What next? 92
2.13 Key terms that I’ve discovered 92
Smart Alex’s tasks 93
DISCOVERING STATISTICS USING IBM SPSS STATISTICS
3 THE PHOENIX OF STATISTICS 95
3.1 What will this chapter tell me? 96
3.2 Problems with NHST 97
3.3 NHST as part of wider problems with science 104
3.4 A phoenix from the EMBERS 111
3.5 Sense, and how to use it 111
3.6 Pre-registering research and open science 117
3.7 Effect sizes 113
3.8 Bayesian approaches 122
3.9 Reporting effect sizes and Bayes factors 131
3.10 Brian s attempt to woo Jane 132
3.11 What next? 4 еъ·?·..
3.12 Key terms that I’ve discovered 133
Smart Alex’s tasks 134
THE IBM SPSS STATISTICS ENVIRONMENT 135
4.1 What will this chapter tell me? 136
4.2 Versions of IBM SPSS Statistics 137
4.3 Windows, Mac OS, and Linux 127
4.4 Getting started •f. - j ;_;j
4.5 The data editor 1 3՝· .
4.6 Entering data into IBM SPSS Statistics 144
4.7 Importing data 156
4.8 The SPSS viewer 157
4.9 Exporting SPSS output 103
4.10 The syntax editor 162
4.11 Saving files 164
4.12 Opening files 165
4.13 Extending IBM SPSS Statistics 166
4.14 Brian s attempt to woo Jane 171
4.15 What next? 172
4.16 Key terms that I’ve discovered 172
Smart Alex’s tasks 173
EXPLORING DATA WITH GRAPHS 17?
5.1 What will this chapter tell me? 178
5.2 The art of presenting data 179
5.3 The SPSS Chart Builder 181
5.4 Histograms 184
5.5 Boxplots (box-whisker diagrams) 192
5.6 Graphing means: bar charts and error bars 194
5.7 Line charts 207
5.8 Graphing relationships: the scatterplot 208
5.9 Editing graphs 218
5.10 Brian’s attempt to woo Jane 221
5.11 What next? 222
viii
EXTENDED CONTENTS
5.12 Key terms that I’ve discovered 222
Smart Alex’s tasks 223
6 THE BEAST OF BIAS 225
6.1 What will this chapter tell me? 226
6.2 What is bias? 227
6.3 Outliers 227
6.4 Overview of assumptions 229
6.5 Additivity and linearity 230
6.6 Normally distributed something or other 230
6.7 Homoscedasticity/homogeneity of variance 237
6.8 Independence 239
6.9 Spotting outliers 240
6.10 Spotting normality 243
6.11 Spotting linearity and heteroscedasticity/heterogeneity of variance 257
6.12 Reducing bias 262
6.13 Brian’s attempt to woo Jane 276
6.14 What next? 277
6.15 Key terms that I’ve discovered 278
Smart Alex’s tasks 278
7 NON-PARAMETRIC MODELS 281
7.1 What will this chapter tell me? 282
7.2 When to use non-parametric tests 283
7.3 General procedure of non-parametric tests using SPSS Statistics 284
7.4 Comparing two independent conditions: the Wilcoxon rank-sum
test and Mann-Whitney test 285
7.5 Comparing two related conditions: the Wilcoxon signed-rank test 297
7.6 Differences between several independent groups: the Kruskal-Wallis test 306
7.7 Differences between several related groups: Friedman’s ANOVA 321
7.8 Brian’s attempt to woo Jane 329
7.9 What next? 331
7.10 Key terms that I’ve discovered 331
Smart Alex’s tasks 331
8 CORRELATION 333
8.1 What will this chapter tell me? 334
8.2 Modelling relationships 335
8.3 Data entry for correlation analysis 342
8.4 Bivariate correlation 344
8.5 Partial and semi-partial correlation 355
8.6 Comparing correlations 362
8.7 Calculating the effect size 363
8.8 How to report correlation coefficents 364
8.9 Brian’s attempt to woo Jane 366
8.10 What next? 367
ix
DISCOVERING STATISTICS USING IBM SPSS STATISTICS
8.11 Key terms that I’ve discovered
Smart Alex’s tasks
9 THE LINEAR MODEL (REGRESSION)
9.1 What will this chapter tell me?
9.2 An introduction to the linear model (regression)
9.3 Bias in linear models?
9.4 Generalizing the model
9.5 Sample size and the linear model
9.6 Fitting linear models: the general procedure
9.7 Using SPSS Statistics to fit a linear model with one predictor
9.8 Interpreting a linear model with one predictor
9.9 The linear model with two or more predictors
(multiple regression)
9.10 Using SPSS Statistics to fit a linear model with several predictors
9.11 Interpreting a linear model with several predictors
9.12 Robust regression
9.13 Bayesian regression
9.14 Reporting linear models
9.15 Brian’s attempt to woo Jane
9.16 What next?
9.17 Key terms that I’ve discovered
Smart Alex’s tasks
10 COMPARING TWO MEANS
10.1 What will this chapter tell me?
10.2 Looking at differences
10.3 A mischievous example
10.4 Categorical predictors in the linear mode!
10.5 The Mest
10.6 Assumptions of the Mest
10.7 Comparing two means: general procedure
10.8 Comparing two independent means using SPSS Statistics
10.9 Comparing two related means using SPSS Statistics
10.10 Reporting comparisons between two means
10.11 Between groups or repeated measures?
10.12 Brian’s attempt to woo Jane
10.13 What next?
10.14 Key terms that I’ve discovered
Smart Alex’s tasks
11 MODERATION, MEDIATION AND MULTICATEGORY PREDICTORS
11.1 What will this chapter tell me?
11.2 The PROCESS tool
11.3 Moderation: interactions in the linear model
11A Mediation
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EXTENDED CONTENTS
11.5 Categorical predictors in regression 508
11.6 Brian’s attempt to woo Jane 516
11.7 What next? 516
11.8 Key terms that Pve discovered 517
Smart Alex’s tasks 518
12 GLM1: COMPARING SEVERAL INDEPENDENT MEANS 519
12.1 What will this chapter tell me? 520
12.2 Using a linear model to compare several means 521
12.3 Assumptions when comparing means 534
12.4 Planned contrasts (contrast coding) 537
12.5 Post hoc procedures 549
12.6 Comparing several means using SPSS Statistics 551
12.7 Output from one-way independent ANOVA 556
12.8 Robust comparisons of several means 564
12.9 Bayesian comparison of several means 566
12.10 Calculating the effect size 567
12.11 Reporting results from one-way independent ANOVA 568
12.12 Brian’s attempt to woo Jane 568
12.13 What next? 570
12.14 Key terms that I’ve discovered 570
Smart Alex’s tasks 570
13 GLM 2: COMPARING MEANS ADJUSTED FOR OTHER PREDICTORS
(ANALYSIS OF COVARIANCE) 573
13.1 What will this chapter tell me? 574
13.2 What is ANCOVA? 575
13.3 ANCOVA and the general linear model 576
13.4 Assumptions and issues in ANCOVA 580
13.5 Conducting ANCOVA using SPSS Statistics 584
13.6 Interpreting ANCOVA 591
13.7 Testing the assumption of homogeneity of regression slopes 598
13.8 Robust ANCOVA 600
13.9 Bayesian analysis with covariates 601
13.10 Calculating the effect size 602
13.11 Reporting results 603
13.12 Brian’s attempt to woo Jane 603
13.13 What next? 604
13.14 Key terms that Pve discovered 605
Smart Alex’s tasks 605
14 GLM 3: FACTORIAL DESIGNS 607
14.1 What will this chapter tell me? 608
14.2 Factorial designs 609
14.3 Independent factorial designs and the linear model 609
14.4 Model assumptions in factorial designs 620
14.5 Factorial designs using SPSS Statistics 620
X!
DISCOVERING STATISTICS USING IBM SPSS STATISTICS
14.6 Output from factorial designs 627
14.7 Interpreting interaction graphs 635
14.8 Robust models of factorial designs 638
14.9 Bayesian models of factorial designs 641
14.10 Calculating effect sizes 643
14.11 Reporting the results of factorial designs 645
14.12 Brian’s attempt to woo Jane 646
14.13 What next? 647
14.14 Key terms that ľve discovered 647
Smart Alex’s tasks 647
15 GLM 4: REPEATED-MEASURES DESIGNS 649
15.1 What will this chapter tell me? 650
15.2 Introduction to repeated-measures designs 651
15.3 A grubby example 652
15.4 Repeated-measures and the linear model 652
15.5 The ANOVA approach to repeated-measures designs 654
15.6 The F-statistic for repeated-measures designs 658
15.7 Assumptions in repeated-measures designs 663
15.8 One-way repeated-measures designs using SPSS 664
15.9 Output for one-way repeated-measures designs 668
15.10 Robust tests of one-way repeated-measures designs 676
15.11 Effect sizes for one-way repeated-measures designs 678
15.12 Reporting one-way repeated-measures designs 679
15.13 A boozy example: a factorial repeated-measures design 680
15.14 Factorial repeated-measures designs using SPSS Statistics 681
15.15 Interpreting factorial repeated-measures designs 687
15.16 Effect sizes for factorial repeated-measures designs 698
15.17 Reporting the results from factorial repeated-measures designs 698
15.18 Brian’s attempt to woo Jane 700
15.19 What next? 701
15.20 Key terms that I’ve discovered 701
Smart Alex’s tasks 701
16 GLM 5 : MIXED DESIGNS 703
16.1 What will this chapter tell me? 704
16.2 Mixed designs 705
16.3 Assumptions in mixed designs 705
16.4 A speed-dating example 706
16.5 Mixed designs using SPSS Statistics 708
16.6 Output for mixed factorial designs 713
16.7 Calculating effect sizes 727
16.8 Reporting the results of mixed designs 729
16.9 Brian’s attempt to woo Jane 732
16.10 What next? 733
16.11 Key terms that I’ve discovered 733
Smart Alex’s tasks 733
xii
EXTENDED CONTENTS
17 MULTIVARIATE ANALYSIS OF VARIANCE (MANOVA) 735
17.1 What will this chapter tell me? 736
17.2 Introducing MANOVA 737
17.3 Introducing matrices 739
17-4 The theory behind MANOVA 741
17.5 Practical issues when conducting MANOVA 753
17.6 MANOVA using SPSS Statistics 755
17.7 Interpreting MANOVA 757
17.8 Reporting results from MANOVA 762
17.9 Following up MANOVA with discriminant analysis 765
17.10 Interpreting discriminant analysis 767
17.11 Reporting results from discriminant analysis 771
17.12 The final interpretation 771
17.13 Brian’s attempt to woo Jane 772
17.14 What next? 773
17.15 Key terms that l։ve discovered 775
Smart Alex’s tasks 775
18 EXPLORATORY FACTOR ANALYSIS 777
18.1 What will this chapter tell me? 778
18.2 When to use factor analysis 779
18.3 Factors and components 780
18.4 Discovering factors 787
18.5 An anxious example 795
18.6 Factor analysis using SPSS Statistics 600
18.7 Interpreting factor analysis 806
18.8 How to report factor analysis 819
18.9 Reliability analysis 821
18.10 Reliability analysis using SPSS Statistics 824
18.11 Interpreting reliability analysis 826
18.12 How to report reliability analysis 830
18.13 Brian’s attempt to woo Jane 831
18.14 What next? 831
18.15 Key terms that I’ve discovered 831
Smart Alex’s tasks 832
19 CATEGORICAL OUTCOMES: CHI-SQUARE AND LOGLINEAR ANALYSIS 835
19.1 What will this chapter tell me? 836
19.2 Analysing categorical data 837
19.3 Associations between two categorical variables 837
19.4 Associations between several categorical variables: loglinear analysis 846
19.5 Assumptions when analysing categorical data 849
19.6 General procedure for analysing categorical outcomes 850
19.7 Doing chi-square using SPSS Statistics 850
19.8 Interpreting the chi-square test 854
19.9 Loglinear analysis using SPSS Statistics 864
xiii
DISCOVERING STATISTICS USING IBM SPSS STATISTICS
19.10 Interpreting loglinear analysis 866
19.11 Reporting the results of loglinear analysis 872
19.12 Brian’s attempt to woo Jane 872
19.13 What next? 874
19.14 Key terms that I’ve discovered 875
Smart Alex’s tasks 875
20 CATEGORICAL OUTCOMES: LOGISTIC REGRESSION 877
20.1 What will this chapter tell me? 878
20.2 What is logistic regression? 879
20.3 Theory of logistic regression 879
20.4 Sources of bias and common problems 886
20.5 Binary logistic regression 891
20.6 Interpreting logistic regression 900
20.7 Reporting logistic regression 911
20.8 Testing assumptions: another example 911
20.9 Predicting several categories: multinomial logistic regression 916
20.10 Reporting multinomial logistic regression 930
20.11 Brian’s attempt to woo Jane 930
20.12 What next? 932
20.13 Key terms that I’ve discovered 932
Smart Alex’s tasks 933
21 MULTILEVEL LINEAR MODELS 935
21.1 What will this chapter tell me? 936
21.2 Hierarchical data 937
21.3 Theory of multilevel linear models 941
21.4 The multilevel model 944
21.5 Some practical issues 948
21.6 Multilevel modelling using SPSS Statistics 951
21.7 Growth models 972
21.8 How to report a multilevel model 987
21.9 A message from the octopus of inescapable despair 988
21.10 Brian’s attempt to woo Jane 988
21.11 What next? 988
21.12 Key terms that I’ve discovered 990
Smart Alex’s tasks 990
EPILOGUE 991
APPENDIX 995
GLOSSARY 1007
REFERENCES 1043
INDEX 1057
XIV
|
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| discipline | Allgemeines Sport Informatik Soziologie Psychologie Mathematik Wirtschaftswissenschaften |
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| genre | (DE-588)4123623-3 Lehrbuch gnd-content |
| genre_facet | Lehrbuch |
| id | DE-604.BV044507233 |
| illustrated | Illustrated |
| indexdate | 2025-02-20T06:44:24Z |
| institution | BVB |
| isbn | 9781526419514 9781526445766 1526419513 9781526419521 9781526436566 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029907115 |
| oclc_num | 989950838 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-355 DE-BY-UBR DE-634 DE-N32 DE-29T DE-20 DE-1050 DE-523 DE-M347 DE-863 DE-BY-FWS DE-11 DE-739 DE-578 DE-19 DE-BY-UBM DE-91 DE-BY-TUM DE-703 DE-573 DE-29 DE-706 DE-N2 DE-M49 DE-BY-TUM DE-1043 DE-945 DE-858 DE-859 DE-384 DE-83 DE-M490 DE-188 DE-860 DE-Aug4 DE-824 DE-862 DE-BY-FWS DE-M29 DE-1047 |
| owner_facet | DE-473 DE-BY-UBG DE-355 DE-BY-UBR DE-634 DE-N32 DE-29T DE-20 DE-1050 DE-523 DE-M347 DE-863 DE-BY-FWS DE-11 DE-739 DE-578 DE-19 DE-BY-UBM DE-91 DE-BY-TUM DE-703 DE-573 DE-29 DE-706 DE-N2 DE-M49 DE-BY-TUM DE-1043 DE-945 DE-858 DE-859 DE-384 DE-83 DE-M490 DE-188 DE-860 DE-Aug4 DE-824 DE-862 DE-BY-FWS DE-M29 DE-1047 |
| physical | xxix, 1070 Seiten Illustrationen, Diagramme |
| publishDate | 2018 |
| publishDateSearch | 2018 |
| publishDateSort | 2018 |
| publisher | SAGE |
| record_format | marc |
| spellingShingle | Field, Andy 1973- Discovering statistics using IBM SPSS statistics handbooks cabt statistics cabt usage cabt data analysis cabt learning cabt education cabt data processing cabt statistical analysis cabt statistical data cabt mathematics cabt Statistik (DE-588)4056995-0 gnd SPSS (DE-588)4056588-9 gnd |
| subject_GND | (DE-588)4056995-0 (DE-588)4056588-9 (DE-588)4123623-3 |
| title | Discovering statistics using IBM SPSS statistics |
| title_alt | Discovering statistics using SPSS |
| title_auth | Discovering statistics using IBM SPSS statistics |
| title_exact_search | Discovering statistics using IBM SPSS statistics |
| title_full | Discovering statistics using IBM SPSS statistics Andy Field |
| title_fullStr | Discovering statistics using IBM SPSS statistics Andy Field |
| title_full_unstemmed | Discovering statistics using IBM SPSS statistics Andy Field |
| title_short | Discovering statistics using IBM SPSS statistics |
| title_sort | discovering statistics using ibm spss statistics |
| topic | handbooks cabt statistics cabt usage cabt data analysis cabt learning cabt education cabt data processing cabt statistical analysis cabt statistical data cabt mathematics cabt Statistik (DE-588)4056995-0 gnd SPSS (DE-588)4056588-9 gnd |
| topic_facet | handbooks statistics usage data analysis learning education data processing statistical analysis statistical data mathematics Statistik SPSS Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029907115&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT fieldandy discoveringstatisticsusingspss AT fieldandy discoveringstatisticsusingibmspssstatistics |
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