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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