Marketing research with SPSS:
Saved in:
| Format: | Book |
|---|---|
| Language: | English |
| Published: |
Harlow [u.a.]
Prentice Hall Financial Times
2008
|
| Edition: | 1. publ. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | X, 441 S. Ill., graph. Darst. |
| ISBN: | 9780273703839 0273703838 |
Staff View
MARC
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Record in the Search Index
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| adam_text | Contents
Preface ix
0 Statistical analyses for marketing
research: when and how to use them 1
Descriptive statistics 1
Univariate statistics 2
Multivariate statistics 3
1 Working with SPSS 7
Chapter objectives 7
General , 7
Data input 7
Typing data directly into SPSS 9
Inputting data from other application programs 11
Data editing 11
Creating labels 11
Working with missing values 13
Creating/calculating a new variable 14
Research on a subset of observations 16
Recoding variables 19
Further reading 22
2 Descriptive statistics 23
Chapter objectives 23
Introduction 23
Frequency tables and graphs 25
Multiple response tables 38
Mean and dispersion 44
Further reading 46
3 Univariate tests 47
Chapter objectives 47
General 47
One sample 48
Nominal variables: Binomial test (z-test for proportion) 48
Nominal variables: test 50
Ordinal variables: Kolmogorov-Smirnov test 52
Interval scaled variables: Z-test or t-test for the mean 52
Two dependent samples 54
Nominal variables: McNemar test 54
Ordinal variables: Wilcoxon test 57
Interval scaled variables: t-test for paired observations 58
Two independent samples
Nominal variables: ~ test °f independence
60
(cross-table analysis) 60
Ordinal variables: Mann-Whitney U test 65
Interval scaled variables: t-test for independent
samples 66
K independent samples 68
Nominal variables: ~ test of independence 68
Ordinal variables: Kruskal-Wallis test 68
Interval scaled variables: Analysis of variance 68
K dependent samples 68
Nominal variables: Cochran Q 68
Ordinal variables: Friedman test 70
Interval scaled variables: Repeated measures
analysis of variance 70
Further reading 70
4 Analysis of variance 71
Chapter objectives 71
Technique 71
Example 1: Analysis of variance as a test
of difference or one-way ANOVA 72
Managerial problem 72
Problem 72
Solution 73
SPSS commands 73
Interpretation of the SPSS output 75
Example 2: Analysis of variance with a
covariate (ANCOVA) 77
Technique: supplement 77
Managerial problem 78
Problem 78
Solution 79
SPSS commands 79
Interpretation of the SPSS output 82
Example 3: Analysis of variance for a
complete 2x2x2 factorial design 92
Managerial problem 92
Problem 93
Solution 93
SPSS commands 93
Interpretation of the SPSS output 96
CONTENTS
Example 4: Multivariate analysis of
variance (MANOVA) 108
Technique: supplement 108
Managerial problem 108
Problem 109
Solution 110
SPSS commands 110
Interpretation of the SPSS output 113
Example 5: Analysis of variance with
repeated measures 120
Managerial problem 120
Problem 122
Solution 122
SPSS commands 122
Interpretation of the SPSS output 125
Example 6: Analysis of variance with
repeated measures and between-subjects
factor 129
Managerial problem 129
Problem 129
Solution 129
SPSS commands 129
Interpretation of the SPSS output 131
Further reading 136
Endnote 136
5 Linear regression analysis 137
Chapter objectives 137
Technique 137
Example 1: A cross-section analysis 141
Managerial problem 141
Problem 142
Solution 142
SPSS commands 142
Interpretation of the SPSS output 150
Example 2: The Stepwise method,
in addition to the Enter method 174
Problem 174
Solution 175
SPSS commands 175
Interpretation of the SPSS output 175
Example 3: The presence of a nominal
variable in the regression model 179
Problem 179
Solution 179
SPSS commands 179
Interpretation of the SPSS output 181
Further reading 183
Endnotes 183
6 Logistic regression analysis 184
Chapter objectives 184
Technique 184
Example 1: Interval-scaled and categorical
independent variables, without interaction
term 187
Managerial problem 187
Problem 187
Solution 188
SPSS commands 188
Interpretation of the SPSS output 192
Example 2: Interval-scaled and categorical
independent variables, with interaction
term 206
Managerial problem 206
Problem 207
Solution 208
SPSS commands 210
Interpretation of the SPSS output 220
Important guidelines 229
One last remark 229
Example 3: The stepwise method,
in addition to the enter method, and
more than one block 230
Managerial problem 230
Problem 230
Solution 230
SPSS commands 230
Interpretation of the SPSS output 233
Example 4: Categorical independent
variables with more than two categories 237
Managerial problem 237
Problem 237
Solution 238
SPSS commands 238
Interpretation of the SPSS output 241
Further reading 243
Endnotes 244
7 Exploratory factor analysis 245
Chapter objectives 245
Technique 245
Example: Exploratory factor analysis 249
Managerial problem 249
Problem 250
Solution 251
SPSS commands 251
Interpretation of the SPSS output 255
Further reading 278
Endnote 278
CONTENTS VII
8 Confirmatory factor analysis and
path analysis using SEM 279
Chapter objectives 279
Technique 279
Example 1: Confirmatory factor analysis 281
Managerial problem 281
Problem 282
Solution 282
AMOS commands 282
Interpretation of the AMOS output 294
Example 2: Path analysis 311
Problem 311
Solution 311
AMOS commands 311
Interpretation of the AMOS output 312
Further reading 316
9 Cluster analysis 317
Chapter objectives 317
Technique 317
Example 1: Cluster analysis with binary
attributes - hierarchical clustering 319
Managerial problem 319
Problem 320
Solution 320
SPSS Commands 320
Interpretation of the SPSS output 324
Example 2: Cluster analysis with continuous
attributes - hierarchical clustering as input
for K-means clustering 342
Managerial problem 342
Problem 342
Solution 343
SPSS commands: Hierarchical clustering 344
Interpretation of the SPSS output: Hierarchical
clustering 347
SPSS commands: K-means clustering 353
Interpretation of the SPSS output: K-means
clustering 355
Further reading 362
Endnotes 362
10 Multidimensional scaling techniques 363
Chapter objectives 363
Technique 363
The form of the data matrix: the number of
ways and the number of modes 363
The technique: the measurement level of the input
and output and the representation of the data 366
Data collection method: direct or indirect
measurement 368
Example 1: Two-way, two-mode
MDS - correspondence analysis 370
Technique: supplement 370
Managerial problem 370
Problem 373
Solution 373
SPSS Commands 373
Interpretation of the SPSS output 384
Example 2: Three-way, two-mode
MDS - two-way, one-mode MDS using
replications in PROXSCAL 398
Managerial problem 398
Technique: supplement 400
Problem 401
Solution 402
SPSS commands: data specification 402
SPSS commands: dimensionality of the solution 404
Interpretation of the SPSS output: dimensionality
of the solution 407
Further reading 415
Website reference 415
Endnotes 416
11 Conjoint analysis 417
Chapter objectives 417
Technique 417
Example: Conjoint analysis 418
Managerial problem 418
Problem 419
Solution 419
SPSS commands 419
Interpretation of the SPSS output 428
Further reading 433
Index
435
|
| adam_txt |
Contents
Preface ix
0 Statistical analyses for marketing
research: when and how to use them 1
Descriptive statistics 1
Univariate statistics 2
Multivariate statistics 3
1 Working with SPSS 7
Chapter objectives 7
General , 7
Data input 7
Typing data directly into SPSS 9
Inputting data from other application programs 11
Data editing 11
Creating labels 11
Working with missing values 13
Creating/calculating a new variable 14
Research on a subset of observations 16
Recoding variables 19
Further reading 22
2 Descriptive statistics 23
Chapter objectives 23
Introduction 23
Frequency tables and graphs 25
Multiple response tables 38
Mean and dispersion 44
Further reading 46
3 Univariate tests 47
Chapter objectives 47
General 47
One sample 48
Nominal variables: Binomial test (z-test for proportion) 48
Nominal variables: \' test 50
Ordinal variables: Kolmogorov-Smirnov test 52
Interval scaled variables: Z-test or t-test for the mean 52
Two dependent samples 54
Nominal variables: McNemar test 54
Ordinal variables: Wilcoxon test 57
Interval scaled variables: t-test for paired observations 58
Two independent samples
Nominal variables: \~ test °f independence
60
(cross-table analysis) 60
Ordinal variables: Mann-Whitney U test 65
Interval scaled variables: t-test for independent
samples 66
K independent samples 68
Nominal variables: \~ test of independence 68
Ordinal variables: Kruskal-Wallis test 68
Interval scaled variables: Analysis of variance 68
K dependent samples 68
Nominal variables: Cochran Q 68
Ordinal variables: Friedman test 70
Interval scaled variables: Repeated measures
analysis of variance 70
Further reading 70
4 Analysis of variance 71
Chapter objectives 71
Technique 71
Example 1: Analysis of variance as a test
of difference or one-way ANOVA 72
Managerial problem 72
Problem 72
Solution 73
SPSS commands 73
Interpretation of the SPSS output 75
Example 2: Analysis of variance with a
covariate (ANCOVA) 77
Technique: supplement 77
Managerial problem 78
Problem 78
Solution 79
SPSS commands 79
Interpretation of the SPSS output 82
Example 3: Analysis of variance for a
complete 2x2x2 factorial design 92
Managerial problem 92
Problem 93
Solution 93
SPSS commands 93
Interpretation of the SPSS output 96
CONTENTS
Example 4: Multivariate analysis of
variance (MANOVA) 108
Technique: supplement 108
Managerial problem 108
Problem 109
Solution 110
SPSS commands 110
Interpretation of the SPSS output 113
Example 5: Analysis of variance with
repeated measures 120
Managerial problem 120
Problem 122
Solution 122
SPSS commands 122
Interpretation of the SPSS output 125
Example 6: Analysis of variance with
repeated measures and between-subjects
factor 129
Managerial problem 129
Problem 129
Solution 129
SPSS commands 129
Interpretation of the SPSS output 131
Further reading 136
Endnote 136
5 Linear regression analysis 137
Chapter objectives 137
Technique 137
Example 1: A cross-section analysis 141
Managerial problem 141
Problem 142
Solution 142
SPSS commands 142
Interpretation of the SPSS output 150
Example 2: The 'Stepwise' method,
in addition to the 'Enter' method 174
Problem 174
Solution 175
SPSS commands 175
Interpretation of the SPSS output 175
Example 3: The presence of a nominal
variable in the regression model 179
Problem 179
Solution 179
SPSS commands 179
Interpretation of the SPSS output 181
Further reading 183
Endnotes 183
6 Logistic regression analysis 184
Chapter objectives 184
Technique 184
Example 1: Interval-scaled and categorical
independent variables, without interaction
term 187
Managerial problem 187
Problem 187
Solution 188
SPSS commands 188
Interpretation of the SPSS output 192
Example 2: Interval-scaled and categorical
independent variables, with interaction
term 206
Managerial problem 206
Problem 207
Solution 208
SPSS commands 210
Interpretation of the SPSS output 220
Important guidelines 229
One last remark 229
Example 3: The 'stepwise' method,
in addition to the 'enter' method, and
more than one 'block' 230
Managerial problem 230
Problem 230
Solution 230
SPSS commands 230
Interpretation of the SPSS output 233
Example 4: Categorical independent
variables with more than two categories 237
Managerial problem 237
Problem 237
Solution 238
SPSS commands 238
Interpretation of the SPSS output 241
Further reading 243
Endnotes 244
7 Exploratory factor analysis 245
Chapter objectives 245
Technique 245
Example: Exploratory factor analysis 249
Managerial problem 249
Problem 250
Solution 251
SPSS commands 251
Interpretation of the SPSS output 255
Further reading 278
Endnote 278
CONTENTS VII
8 Confirmatory factor analysis and
path analysis using SEM 279
Chapter objectives 279
Technique 279
Example 1: Confirmatory factor analysis 281
Managerial problem 281
Problem 282
Solution 282
AMOS commands 282
Interpretation of the AMOS output 294
Example 2: Path analysis 311
Problem 311
Solution 311
AMOS commands 311
Interpretation of the AMOS output 312
Further reading 316
9 Cluster analysis 317
Chapter objectives 317
Technique 317
Example 1: Cluster analysis with binary
attributes - hierarchical clustering 319
Managerial problem 319
Problem 320
Solution 320
SPSS Commands 320
Interpretation of the SPSS output 324
Example 2: Cluster analysis with continuous
attributes - hierarchical clustering as input
for K-means clustering 342
Managerial problem 342
Problem 342
Solution 343
SPSS commands: Hierarchical clustering 344
Interpretation of the SPSS output: Hierarchical
clustering 347
SPSS commands: K-means clustering 353
Interpretation of the SPSS output: K-means
clustering 355
Further reading 362
Endnotes 362
10 Multidimensional scaling techniques 363
Chapter objectives 363
Technique 363
The form of the data matrix: the number of
ways and the number of modes 363
The technique: the measurement level of the input
and output and the representation of the data 366
Data collection method: direct or indirect
measurement 368
Example 1: Two-way, two-mode'
MDS - correspondence analysis 370
Technique: supplement 370
Managerial problem 370
Problem 373
Solution 373
SPSS Commands 373
Interpretation of the SPSS output 384
Example 2: 'Three-way, two-mode'
MDS - 'two-way, one-mode' MDS using
replications in PROXSCAL 398
Managerial problem 398
Technique: supplement 400
Problem 401
Solution 402
SPSS commands: data specification 402
SPSS commands: dimensionality of the solution 404
Interpretation of the SPSS output: dimensionality
of the solution 407
Further reading 415
Website reference 415
Endnotes 416
11 Conjoint analysis 417
Chapter objectives 417
Technique 417
Example: Conjoint analysis 418
Managerial problem 418
Problem 419
Solution 419
SPSS commands 419
Interpretation of the SPSS output 428
Further reading 433
Index
435 |
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| index_date | 2024-07-02T22:13:34Z |
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| publisher | Prentice Hall Financial Times |
| record_format | marc |
| spelling | Marketing research with SPSS Wim Janssens ... 1. publ. Harlow [u.a.] Prentice Hall Financial Times 2008 X, 441 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier SPSS for Windows Marktonderzoek gtt SPSS gtt Marketing research Marktforschung (DE-588)4037630-8 gnd rswk-swf Marketingforschung (DE-588)4200055-5 gnd rswk-swf SPSS (DE-588)4056588-9 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Marktforschung (DE-588)4037630-8 s Statistik (DE-588)4056995-0 s SPSS (DE-588)4056588-9 s DE-188 Marketingforschung (DE-588)4200055-5 s Janssens, Wim Sonstige oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016767227&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Marketing research with SPSS SPSS for Windows Marktonderzoek gtt SPSS gtt Marketing research Marktforschung (DE-588)4037630-8 gnd Marketingforschung (DE-588)4200055-5 gnd SPSS (DE-588)4056588-9 gnd Statistik (DE-588)4056995-0 gnd |
| subject_GND | (DE-588)4037630-8 (DE-588)4200055-5 (DE-588)4056588-9 (DE-588)4056995-0 |
| title | Marketing research with SPSS |
| title_auth | Marketing research with SPSS |
| title_exact_search | Marketing research with SPSS |
| title_exact_search_txtP | Marketing research with SPSS |
| title_full | Marketing research with SPSS Wim Janssens ... |
| title_fullStr | Marketing research with SPSS Wim Janssens ... |
| title_full_unstemmed | Marketing research with SPSS Wim Janssens ... |
| title_short | Marketing research with SPSS |
| title_sort | marketing research with spss |
| topic | SPSS for Windows Marktonderzoek gtt SPSS gtt Marketing research Marktforschung (DE-588)4037630-8 gnd Marketingforschung (DE-588)4200055-5 gnd SPSS (DE-588)4056588-9 gnd Statistik (DE-588)4056995-0 gnd |
| topic_facet | SPSS for Windows Marktonderzoek SPSS Marketing research Marktforschung Marketingforschung Statistik |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016767227&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT janssenswim marketingresearchwithspss |