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Statistics for Marketing and Consumer Research
ISBN-13:
9781473903524
Veröffentl:
2008
Einband:
EPUB
Seiten:
432
Autor:
Mario Mazzocchi
eBook Typ:
EPUB
eBook Format:
Reflowable EPUB
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:
Simple-to-follow, yet rigorous, practical guide to the statistical techniques used in marketing and consumer research.
Balancing simplicity with technical rigour, this practical guide to the statistical techniques essential to research in marketing and related fields, describes each method as well as showing how they are applied.
The book is accompanied by two real data sets to replicate examples and with exercises to solve, as well as detailed guidance on the use of appropriate software including:
- 750 powerpoint slides with lecture notes and step-by-step guides to run analyses in SPSS (also includes screenshots)
- 136 multiple choice questions for tests
This is augmented by in-depth discussion of topics including:
- Sampling
- Data management and statistical packages
- Hypothesis testing
- Cluster analysis
- Structural equation modelling
PART ONE: COLLECTING, PREPARING AND CHECKING THE DATA
Measurement, Errors and Data for Consumer Research
Secondary Consumer Data
Primary Data Collection
Data Preparation and Descriptive Statistics
PART TWO: SAMPLING, PROBABILITY AND INFERENCE
Sampling
Hypothesis Testing
Analysis of Variance
PART THREE: RELATIONSHIPS AMONG VARIABLES
Correlation and Regression
Association, Log-linear Analysis and Canonical Correlation Analysis
Factor Analysis and Principal Component Analysis
PART FOUR: CLASSIFICATION AND SEGMENTATION TECHNIQUES
Discriminant Analysis
Cluster Analysis
Multidimensional Scaling
Correspondence Analysis
PART FIVE: FURTHER METHODS IN MULTIVARIATE ANALYSIS
Structural Equation Models
Discrete Choice Models
The End (and Beyond)
Measurement, Errors and Data for Consumer Research
Secondary Consumer Data
Primary Data Collection
Data Preparation and Descriptive Statistics
PART TWO: SAMPLING, PROBABILITY AND INFERENCE
Sampling
Hypothesis Testing
Analysis of Variance
PART THREE: RELATIONSHIPS AMONG VARIABLES
Correlation and Regression
Association, Log-linear Analysis and Canonical Correlation Analysis
Factor Analysis and Principal Component Analysis
PART FOUR: CLASSIFICATION AND SEGMENTATION TECHNIQUES
Discriminant Analysis
Cluster Analysis
Multidimensional Scaling
Correspondence Analysis
PART FIVE: FURTHER METHODS IN MULTIVARIATE ANALYSIS
Structural Equation Models
Discrete Choice Models
The End (and Beyond)