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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…mehr
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
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Mario Mazzocchi is Associate Professor in Statistics and Economics at the Department of Statistical Sciences of the University of Bologna. He is also Visiting Research Fellow at the University of Reading, where he has previously served as a lecturer in Applied Economics and Consumer Behaviour. He is currently a consultant to FAO on nutrition policies, and has been appointed by the European Commission as a permanent member of the group of experts on the evaluation of the EU School Fruit Scheme. He is Associate Editor of the journal Food Policy. He has led research teams of the University of Bologna in four EC-funded research projects. He has published two books(Fat Economics and Statistics for Marketing and Consumer Research) and about 40 articles in international refereed papers on a variety of applied economics topics, including consumer research, policy evaluation, health economics, tourism economics, time series econometrics.
Inhaltsangabe
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)
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)
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)
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)
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