Statistics for marketing and consumer research

Table of Content 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)

Balancing simplicity with technical rigour, this practical guide to the statistical techniques essential to research in marketing and related fields, describes each methods as well as showing how they are applied. Real data sets and detailed guidance on the use of appropriate software is included along with discussion of: - Sampling - Data management an statistical packages - Hypothesis testing - Cluster analysis - Structural equation modelling (https://us.sagepub.com/en-us/nam/statistics-for-marketing-and-consumer-research/book228010)