ABSTRACT: WidgeCorps’s management team had a lack in understand of some of the key multivariate statistical techniques used by many companies to measure how variables react with one another. This paper will discuss how three of these techniques are commonly used and provides a recommendation for the company to use as they move forward with research and development of new products. This paper also compares and contrasts the different multivariate techniques. KEYWORDS: multivariate techniques, Chi-Square Test, multidimensional scaling
There are many different multivariate techniques commonly used in businesses across the world. This paper will compare three commonly used techniques including factor analysis, multi-dimensional scaling, and cluster analysis. Additionally, I will provide my recommendation for WidgeCorp to follow as we move forward and dive into the cold beverage market. To begin, it is important to have a clear understanding about why and how a company will use multivariate techniques as part research. The term multivariate technique is somewhat of a blanket-term which includes many different techniques used by statisticians and researchers in many different fields, (Dayton, 2012). Multivariate techniques allow for companies to perform research on more than one variable to determine if there is a relationship between them. For many companies, the multivariate techniques are used to effective measure quality and safety, (Yang, 2010). WidgeCrop will be able to use each of the techniques as we move forward with our new business ventures into the cold beverage market. Factor Analysis:
Factor analysis is one of the many techniques that can be used in different types of research projects. Factor analysis is most often used to compare variables which have a correlation to other confounding variables, (Dayton, 2012). Factor analysis will prove helpful after we have developed our products and are testing the new beverages in different markets. As an example, we could test the hypothesis that WidgeCorp’s new line of cold beverages burns more calories than our competitor Gatorade’s line of cold beverages. The observed variable would include whatever the ingredient is in the beverage which helps to burn calories. The confounding variable could be the level of activity of those participating in the study. As part of my research for this project, I looked into several companies who use factor analysis as part of their research efforts. Companies like Twitter, Facebook, and other social media outlets have been using factor-analysis to help them find the hottest trend, (Du, 2012). These companies generally use a five-step process to help them find the hottest trends. The first step is initial research used to gather data. The second step involves finding key trends or factors. The third step involves defining and interpreting the latest trends, (Du, 2012). The fourth step involves defining the trends/factors into variables. The final step entails projecting how successful the trends will become. By using the factor analysis method, social media outlets are able to successful be a part of the most trendy new products and services used by consumers across the globe. Cluster Analysis:
Cluster Analysis is another technique that Widgecorp will likely use as part of our cold beverages research. Cluster Analysis lumps groups of related characteristics together, (Dayton, 2102). Cluster Analysis would be most helpful to WidgeCorp as part of the beginning stages of the research process. Cluster Analysis uses many different mathematical methods to help determine statistical significance. WidgeCorp will be able to use Cluster Analysis as we dive into market research. We will use Cluster Analysis to determine what populations of people that we should focus our marketing efforts on. When researching Cluster Analysis for this presentation, I came across a few examples of companies who used the Cluster Analysis technique, (Downes,...
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