Management

Multivariate Techniques
Multivariate Techniques
Introduction
A market research company has approached WidgeCorp and is trying to sell them some marketing statistical data. Senior management would like an explanation of multivariate statistics so they can make a decision on whether to buy this data.
Multivariate Statistical Analysis
Multivariate statistical analysis (MSA) is the multiple innovative methods for studying associations among variables at the same time. MSA is used in research that involves more than one dependent variable (outcome of interest), and more than one independent variable (predictor), or both. MSA is often used by researches that hypothesize that a pre-arranged OI (outcome of interest) is prompted or persuaded by more than one entity. There are many types of MST’s (multivariate statistical techniques) used to do analysis among which FA (factor analysis), MDS (multi-dimensional scaling) and CA (cluster analysis) are the most widely used (Hall, 2014).
Factor Analysis
Definition of Factor Analysis (FA)
FA (factor analysis) is defined as a data reduction technique that allows reduction of large amounts of variables to a smaller and more manageable number of factors. It uncovers patterns among the variables and clusters them into interrelated variable factors. Its main purpose is to summarize data and is not predictive (CTUO-3, 2012). After compiling the data on what variables there are on the subject you chose, FA attempts to identify certain criteria that are critical to the analysis with the results being used to determine your outcome (Alley, 2014).
Uses of Factor Analysis (FA)
FA (factor analysis) can be used in virtually all businesses for whatever purpose you need to study a certain amount of data. It can be used in marketing and planning, financing, medical research, industries such as insurance, automotive, engineering, healthcare, and virtually any type of business. It is the most common type of…