Understand Multivariate Analysis

Related Articles

There are 7 articles in our archive related to this topic. Below are 5 selected at random and available to all users of the site.

A survey of multivariate methods useful for market research

Most researchers are already familiar with universal statistical methods. This article discusses multivariate statistical methods, including key characteristics of multivariate procedures and examples.

Multivariate analysis - some vocabulary

People new to multivariate analysis can sometimes feel as though coworkers are speaking a foreign language. Gary Mullet, of the Georgia Institute of Technology, explains some of the requisite vocabulary for multivariate statistics and analysis.

Multivariate and perceptual mapping with discriminant analysis

Discriminant analysis determines what best distinguishes or tells apart groups. This article explains how to develop different types of perceptual maps with discriminant analysis, including point vector maps, the all-group scatter plot, the discriminant “territorial map,” and the vector territorial map. The author suggests several software programs for producing these maps.

Borrowing from one to enrich the other

Once-academic techniques have become increasingly common in everyday quantitative market research. This article discusses three multivariate techniques that have been adapted for qualitative research: conjoint analysis, cluster analysis and multidimensional scaling.

Six questions to ask your supplier about multivariate analysis

The author presents six questions that consumers should ask suppliers of multivariate analysis. Issues addressed include the cleaning and handling of data, the program and process for analyzing the data, the presentation of the final project, and the potential for repeat analyses.

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Recent Articles

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How to make sure your physician surveys are giving you accurate information

In online research with physicians, three parties - the doctors, the client company and the research vendor - are responsible for ensuring data quality. This article outlines steps to follow to ensure that each stakeholder holds up their end of the bargain.

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