Statistics for marketing and consumer research

By:

Mazzocchi, Mario

Material type: Text

TextPublication details: Sage Publications Ltd. London 2008Description: xviii, 412 pISBN:

9781412911221

Subject(s):

DDC classification:

658.83 MAZ

Summary: 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

List(s) this item appears in: HR & OB

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Marketing	658.83 MAZ (Browse shelf(Opens below))	1	Available		005130

Table of contents:

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

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