Marketing Analytics: Statistical Tools for Marketing and Consumer Behaviour using SPSS
Marketing Analytics provides guidelines in the application of statistics using SPSS for students and professionals using quantitative methods in Marketing and Consumer Behaviour. With simple language and a practical, screenshot-led approach, the book presents eleven multivariate techniques and the steps required to perform analysis.
Each chapter contains a brief description of the technique, followed by the possible marketing research applications. One of these applications is then used in detail to illustrate its applicability in a research context, including the needed SPSS commands and illustrations. Each chapter also includes practical exercises, which require the readers to perform the technique and interpret the results, equipping students with the necessary skills to apply statistics, by means of SPSS, in marketing and consumer research. Finally, there is a list of articles employing the technique, which can be used for further reading.
This textbook provides introductory material for advanced undergraduate and postgraduate students studying marketing and consumer analytics, teaching methods along with practical software-applied training using SPSS. Support material includes two real datasets to illustrate the techniques’ applications and PowerPoint slides providing a step-by-step guide to the analysis and commented outcomes. Professionals are invited to use the book to select and use the appropriate analytics for their specific context.
Cover Half Title Series Title Copyright Contents Preface 1 Creating and examining databases in SPSS 1.1 Creating the SPSS spreadsheet and manipulating data 1.2 Descriptive statistics with frequencies 1.3 Cross tabulation 2 Introduction to exploratory data analysis 2.1 Exploratory data analysis 2.2 Verification of assumptions 2.3 Outliers 2.4 Missing values 3 Analysis of variance 3.1 Application of t-test in SPSS 3.2 Theoretical background – analysis of variance (ANOVA) 3.3 Marketing application of ANOVA 3.4 Application of ANOVA in SPSS 3.5 Theoretical background – multivariate analysis of variance (MANOVA) 3.6 Application of MANOVA in SPSS 4 Regression analysis 4.1 Theoretical background – simple regression analysis 4.2 Theoretical background – multiple regression analysis 4.3 Marketing application of regression analysis 4.4 Application of multiple regression in SPSS 5 Time series analysis 5.1 Theoretical background – time series analysis 5.2 Marketing application of time series analysis 5.3 Application of time series analysis in SPSS 6 Discriminant analysis 6.1 Theoretical background – two groups discriminant analysis 6.2 Theoretical background – multiple discriminant analysis 6.3 Marketing application of discriminant analysis 6.4 Application of discriminant analysis in SPSS 6.5 Theoretical background – logistic regression 6.6 Application of logistic regression in SPSS 7 Cluster analysis 7.1 Theoretical background – cluster analysis 7.2 Marketing application of cluster analysis 7.3 Application of cluster analysis in SPSS – hierarchical approach 7.4 Application of cluster analysis in SPSS – nonhierarchical approach 8 Exploratory Factor Analysis (EFA) 8.1 Theoretical background – exploratory factor analysis 8.2 Marketing application of exploratory factor analysis 8.3 Application of exploratory factor analysis in SPSS 9 Confirmatory Factor Analysis (CFA) 9.1 Theoretical background – confirmatory factor analysis 9.2 Marketing application of CFA 9.3 Application of confirmatory factor analysis with AMOS 9.4 The CFA model in AMOS 9.5 The CFA analysis 9.6 The CFA output 10 Structural Equation Modeling (SEM) 10.1 Theoretical background – structural equation modeling 10.2 Marketing application of SEM 10.3 Application of structural equation modeling with AMOS 10.4 The SEM model in AMOS 10.5 The SEM analysis 10.6 The SEM output Appendix 1: Fitness center questionnaire Appendix 2: Supermarket questionnaire Bibliography Index
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