Verfügbarkeit: Statistics for marketing and consumer research

Statistics for marketing and consumer research:

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Bibliographische Detailangaben
1. Verfasser:	Mazzocchi, Mario (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Los Angeles [u.a.] Sage 2008
Ausgabe:	1. publ.
Schlagworte:	Marketing research / Statistical methods Consumers / Research / Statistical methods Marketingforschung Statistik Verbraucherforschung
Online-Zugang:	Inhaltsverzeichnis
Beschreibung:	XVIII, 412 S. graph. Darst.
ISBN:	1412911214 1412911222 9781412911214 9781412911221

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Datensatz im Suchindex

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adam_text	Contents Preface xii List of Acronyms xvii Part I Collecting, Preparing and Checking the Data 1 1 Measurement, Errors and Data for Consumer Research 2 1.1 Measuring the world (of consumers): the problem of measurement 3 1.2 Measurement scales and latent dimensions 6 1.3 Two sample data-sets 11 1.4 Statistical software 18 Summing up 23 Exercises 23 Further readings and web-links 25 Hints for more advanced studies 26 Notes 26 2 Secondary Consumer Data 27 2.1 Primary and secondary data 28 2.2 Secondary data sources 32 2.3 Household budget surveys 36 2.4 Household panels 40 2.5 Commercial and scan data 41 Summing up 43 Exercises 44 Further readings and web-links 45 Hints for more advanced studies 45 Notes 45 3 Primary Data Collection 46 3.1 Primary data collection: surveys errors and the research design 47 3.2 Administration methods 53 3.3 Questionnaire 58 3.4 Four types of surveys 63 Summing up 74 Exercises 75 Further readings and web-links 76 Hints for more advanced studies 76 Notes 76 viii CONTENTS Data Preparation and Descriptive Statistics 77 4.1 Data preparation 78 4.2 Data exploration 85 4.3 Missing values and outliers detection 93 Summing up 100 Exercises 101 Further readings and web-links 102 Hints for more advanced studies 102 Notes 102 Part II Sampling, Probability and Inference 103 5 Sampling 104 5.1 To sample or not to sample 105 5.2 Probability sampling 108 5.3 Non-probability sampling 123 Summing up 125 Appendix 126 Exercises 128 Further readings and web-links 128 Hints for more advanced studies 129 Notes 129 6 Hypothesis Testing 130 6.1 Confidence intervals and the principles of hypothesis testing 130 6.2 Test on one mean 137 6.3 Test on two means 139 6.4 Qualitative variables and non-parametric tests 142 6.5 Tests on proportions and variances 145 Summing up 146 Exercises 147 Further readings and web-links 147 Hints for more advanced studies 148 Notes 148 7 Analysis of Variance 150 7.1 Comparing more than two means: analysis of variance 151 7.2 Further testing issues in one-way ANOVA 154 7.3 Multi-way ANOVA, regression and the general linear model (GLM) 160 7.4 Starting hints for more complex ANOVA designs 162 Summing up 167 Exercises 167 Further readings and web-links 168 Hints for more advanced studies 169 Notes 169 CONTENTS ix Part III Relationships Among Variables 171 8 Correlation and Regression 172 8.1 Covariance and correlation measures 173 8.2 Linear regression 179 8.3 Multiple regression 185 8.4 Stepwise regression 187 8.5 Extending the regression model 189 Summing up 193 Exercises 193 Further readings and web-links 194 Hints for more advanced studies 195 Notes 195 9 Association, Log-linear Analysis and Canonical Correlation Analysis 196 9.1 Contingency tables and association statistics 196 9.2 Log-linear analysis 199 9.3 Canonical correlation analysis 208 Summing up 214 Exercises 215 Further readings and web-links 216 Hints for more advanced studies 216 Notes 217 10 Factor Analysis and Principal Component Analysis 218 10.1 Principles and applications of data reduction techniques 219 10.2 Factor analysis 221 10.3 Principal component analysis 229 10.4 Theory into practice 235 Summing up 244 Exercises 245 Further readings and web-links 246 Hints for more advanced studies 246 Notes 246 Part IV Classification and Segmentation Techniques 247 11 Discriminant Analysis 248 11.1 Discriminant analysis and its application to consumer and marketing data 248 11.2 Running discriminant analysis 250 11.3 Multiple discriminant analysis 254 Summing up 260 Exercises 260 Further readings and web-links 261 Hints for more advanced studies 261 Notes 262 CONTENTS 12 Cluster Analysis 263 12.1 Cluster analysis and its application to consumer and marketing data 263 12.2 Steps in conducting cluster analysis 265 12.3 The application of cluster analysis in SAS and SPSS - empirical issues and solutions 271 Summing up 280 Exercises 280 Further readings and web-links 281 Hints for more advanced studies 281 Notes 282 13 Multidimensional Scaling 283 13.1 Preferences, perceptions and multidimensional scaling 283 13.2 Running multidimensional scaling 286 13.3 Multidimensional scaling and unfolding using SPSS and SAS 292 Summing up 297 Exercises 297 Further readings and web-links 298 Hints for more advanced studies 299 Notes 299 14 Correspondence Analysis 300 14.1 Principles and applications of correspondence analysis 300 14.2 Theory and techniques of correspondence analysis 303 14.3 Running correspondence analysis 305 Summing up 311 Exercises 312 Further readings and web-links 312 Hints for more advanced studies 313 Notes 313 Part V Further Methods in Multivariate Analysis 315 15 Structural Equation Models 316 15.1 From exploration to confirmation: structural equation models 316 15.2 Structural equation modeling: key concepts and estimation 318 15.3 Theory at work: SEM and the Theory of Planned Behavior 322 Summing up 333 Exercises 333 Further readings and web-links 335 Hints for more advanced studies 335 Notes 336 16 Discrete Choice Models 337 16.1 From linear regression to discrete choice models 337 16.2 Discrete choice models 339 CONTENTS xi 16.3 Discrete choice models in SPSS 342 16.4 Choice modeling and conjoint analysis 347 Summing up 349 Exercises 350 Further readings and web-links 351 Hints for more advanced studies 351 17 The End (and Beyond) 352 17.1 Conclusions 353 17.2 Data mining 353 17.3 The Bayesian comeback 354 Summing up 358 Notes 358 Appendix Fundamentals of Matrix Algebra and Statistics 359 A.I Getting to know χ and y 359 A.2 First steps into statistical grounds 367 Notes 374 Glossary 375 References 387 Index 399
adam_txt	Contents Preface xii List of Acronyms xvii Part I Collecting, Preparing and Checking the Data 1 1 Measurement, Errors and Data for Consumer Research 2 1.1 Measuring the world (of consumers): the problem of measurement 3 1.2 Measurement scales and latent dimensions 6 1.3 Two sample data-sets 11 1.4 Statistical software 18 Summing up 23 Exercises 23 Further readings and web-links 25 Hints for more advanced studies 26 Notes 26 2 Secondary Consumer Data 27 2.1 Primary and secondary data 28 2.2 Secondary data sources 32 2.3 Household budget surveys 36 2.4 Household panels 40 2.5 Commercial and scan data 41 Summing up 43 Exercises 44 Further readings and web-links 45 Hints for more advanced studies 45 Notes 45 3 Primary Data Collection 46 3.1 Primary data collection: surveys errors and the research design 47 3.2 Administration methods 53 3.3 Questionnaire 58 3.4 Four types of surveys 63 Summing up 74 Exercises 75 Further readings and web-links 76 Hints for more advanced studies 76 Notes 76 viii CONTENTS Data Preparation and Descriptive Statistics 77 4.1 Data preparation 78 4.2 Data exploration 85 4.3 Missing values and outliers detection 93 Summing up 100 Exercises 101 Further readings and web-links 102 Hints for more advanced studies 102 Notes 102 Part II Sampling, Probability and Inference 103 5 Sampling 104 5.1 To sample or not to sample 105 5.2 Probability sampling 108 5.3 Non-probability sampling 123 Summing up 125 Appendix 126 Exercises 128 Further readings and web-links 128 Hints for more advanced studies 129 Notes 129 6 Hypothesis Testing 130 6.1 Confidence intervals and the principles of hypothesis testing 130 6.2 Test on one mean 137 6.3 Test on two means 139 6.4 Qualitative variables and non-parametric tests 142 6.5 Tests on proportions and variances 145 Summing up 146 Exercises 147 Further readings and web-links 147 Hints for more advanced studies 148 Notes 148 7 Analysis of Variance 150 7.1 Comparing more than two means: analysis of variance 151 7.2 Further testing issues in one-way ANOVA 154 7.3 Multi-way ANOVA, regression and the general linear model (GLM) 160 7.4 Starting hints for more complex ANOVA designs 162 Summing up 167 Exercises 167 Further readings and web-links 168 Hints for more advanced studies 169 Notes 169 CONTENTS ix Part III Relationships Among Variables 171 8 Correlation and Regression 172 8.1 Covariance and correlation measures 173 8.2 Linear regression 179 8.3 Multiple regression 185 8.4 Stepwise regression 187 8.5 Extending the regression model 189 Summing up 193 Exercises 193 Further readings and web-links 194 Hints for more advanced studies 195 Notes 195 9 Association, Log-linear Analysis and Canonical Correlation Analysis 196 9.1 Contingency tables and association statistics 196 9.2 Log-linear analysis 199 9.3 Canonical correlation analysis 208 Summing up 214 Exercises 215 Further readings and web-links 216 Hints for more advanced studies 216 Notes 217 10 Factor Analysis and Principal Component Analysis 218 10.1 Principles and applications of data reduction techniques 219 10.2 Factor analysis 221 10.3 Principal component analysis 229 10.4 Theory into practice 235 Summing up 244 Exercises 245 Further readings and web-links 246 Hints for more advanced studies 246 Notes 246 Part IV Classification and Segmentation Techniques 247 11 Discriminant Analysis 248 11.1 Discriminant analysis and its application to consumer and marketing data 248 11.2 Running discriminant analysis 250 11.3 Multiple discriminant analysis 254 Summing up 260 Exercises 260 Further readings and web-links 261 Hints for more advanced studies 261 Notes 262 CONTENTS 12 Cluster Analysis 263 12.1 Cluster analysis and its application to consumer and marketing data 263 12.2 Steps in conducting cluster analysis 265 12.3 The application of cluster analysis in SAS and SPSS - empirical issues and solutions 271 Summing up 280 Exercises 280 Further readings and web-links 281 Hints for more advanced studies 281 Notes 282 13 Multidimensional Scaling 283 13.1 Preferences, perceptions and multidimensional scaling 283 13.2 Running multidimensional scaling 286 13.3 Multidimensional scaling and unfolding using SPSS and SAS 292 Summing up 297 Exercises 297 Further readings and web-links 298 Hints for more advanced studies 299 Notes 299 14 Correspondence Analysis 300 14.1 Principles and applications of correspondence analysis 300 14.2 Theory and techniques of correspondence analysis 303 14.3 Running correspondence analysis 305 Summing up 311 Exercises 312 Further readings and web-links 312 Hints for more advanced studies 313 Notes 313 Part V Further Methods in Multivariate Analysis 315 15 Structural Equation Models 316 15.1 From exploration to confirmation: structural equation models 316 15.2 Structural equation modeling: key concepts and estimation 318 15.3 Theory at work: SEM and the Theory of Planned Behavior 322 Summing up 333 Exercises 333 Further readings and web-links 335 Hints for more advanced studies 335 Notes 336 16 Discrete Choice Models 337 16.1 From linear regression to discrete choice models 337 16.2 Discrete choice models 339 CONTENTS xi 16.3 Discrete choice models in SPSS 342 16.4 Choice modeling and conjoint analysis 347 Summing up 349 Exercises 350 Further readings and web-links 351 Hints for more advanced studies 351 17 The End (and Beyond) 352 17.1 Conclusions 353 17.2 Data mining 353 17.3 The Bayesian comeback 354 Summing up 358 Notes 358 Appendix Fundamentals of Matrix Algebra and Statistics 359 A.I Getting to know χ and y 359 A.2 First steps into statistical grounds 367 Notes 374 Glossary 375 References 387 Index 399
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title	Statistics for marketing and consumer research
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title_exact_search_txtP	Statistics for marketing and consumer research
title_full	Statistics for marketing and consumer research Mario Mazzocchi
title_fullStr	Statistics for marketing and consumer research Mario Mazzocchi
title_full_unstemmed	Statistics for marketing and consumer research Mario Mazzocchi
title_short	Statistics for marketing and consumer research
title_sort	statistics for marketing and consumer research
topic	Marketing research / Statistical methods Consumers / Research / Statistical methods Marketingforschung (DE-588)4200055-5 gnd Statistik (DE-588)4056995-0 gnd Verbraucherforschung (DE-588)4187567-9 gnd
topic_facet	Marketing research / Statistical methods Consumers / Research / Statistical methods Marketingforschung Statistik Verbraucherforschung
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