Statistics provide the frameworks for quantitative studies in marketing analytics and research. They are the guard rails that reveal the significance and accuracy of the results. Techniques such as perceptual maps, cluster analysis, factor analysis, regression and market response models provide for greater clarity, and permit deeper analysis and visualization of data.
This chapter reviews the statistical techniques and frameworks that are of greater relevance to research and analytics, including probability theory, Bayes theorem, discrete and continuous data distributions, hypothesis testing, correlation, regression and factor analysis.
Some other relevant statistical techniques are covered in other chapters. For instance, cluster analysis (segmentation analysis) in Chapter Segmentation and conjoint analysis in Chapter Product Design
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In an analytics-driven business environment, this analytics-centred consumer marketing workshop is tailored to the needs of consumer analysts, marketing researchers, brand managers, category managers and seasoned marketing and retailing professionals.
Is marketing education fluffy too?
Marketing simulators impart much needed combat experiences, equipping practitioners with the skills to succeed in the consumer market battleground. They combine theory with practice, linking the classroom with the consumer marketplace.