Utilization of Multivariate Statistics in Outdoor Sporting Goods

Ways in which multivariate statistics are utilized outdoor sporting goods
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Contents
Major ways in which multivariate statistics are utilized in this scenario.....................................................2
Examples of a real company has used the techniques..................................................................................6
A summary to upper management...............................................................................................................7
Preferred Technique....................................................................................................................................8
What the manage management will learn from my selection......................................................................8
References...................................................................................................................................................8

Major ways in which multivariate statistics are utilized in this scenario
Multivariate statistics are the techniques that uses two or more variables or factors to
demonstrate various insights from a data for making important decisions and inferences (Jesus,
Beatriz, Beatriz, & Justiniano, 2011). The insights are made about the sample data (Jesus,
Beatriz, Beatriz, & Justiniano, 2011). The insights are used for making inferences or conclusions
about the features or characteristics of the population (Roman, Ravilya, & Ekaterina, 2010).
Multivariate statistics can also be defined as the principles that involves observation and analysis
of two or more variables of the sample (Roman, Ravilya, & Ekaterina, 2010).
The major use of multivariate statistics is for making comparisons, investigating patterns and
relationships between the variables. Multivariate statistics are also used to make predictions of
certain variables (Roman, Ravilya, & Ekaterina, 2010). There are several multivariate statistics
analysis. Some of the known multivariate statistics analysis include; multiple regression analysis,
logistic regression analysis, discriminant analysis, multivariate analysis of variance, factor
analysis, cluster analysis, multidimensional scaling, correspondence analysis, conjoint analysis,
canonical correlation analysis and structural equation modelling (Roman, Ravilya, & Ekaterina,
2010).
A multiple linear regression analysis is a multivariate statistic technique that is used to
investigate the relationship between a single independent variable and two or more independent
variables (Roman, Ravilya, & Ekaterina, 2010). A multiple regression analysis is done to
establish a linear model that can be used to predict the dependent variable using the independent
variables. Multivariate linear regression analysis is mainly applied in forecasting (Jesus, Beatriz,
Beatriz, & Justiniano, 2011).