Phase 4 Group Project Individual Portion



Phase 4 Group Project Individual Portion

Factor Analysis

The core purpose in statistics of using factor analysis is to analyze few contemporary patterns contained by the variables according to their pattern of relationships and variability among the exploratory variables. In particular, factor analysis aims to analyze that if the exploratory variables have been explained in major cases or completely determine the factors of a smaller number of variables with the smaller sample size called factors.

In short, we can say that if two variables have a strong correlation with the same factor, a not insignificant part of the correlation between the two variables is explained by the fact that they have in common that factor. Therefore, a principle of identification of these common factors, factor analysis provides a description in simple form, the complex network of interpolations existing within a set of variables associated. This description is used to define, within the correlation matrix, a limited number of components independent of one another and in the factors identified i.e. they explain the maximum possible variance of the variables contained in the array of original information. Date, therefore, an n x p matrix containing p variables detected on n units, it is necessary to ascertain the extent to which each variable is a repetition of the description made ??by the remaining p-1 and, therefore, if there is a possibility to reach the same descriptive efficacy with a smaller number of unobserved variables called, of course, factors.

There are various statistical methods used in statistics to briefly explain the relationship between independent and dependent variables. The technique of factor analysis is certainly different from the contemporary methods. The basic aim of factor analysis is to analyze the similar or even dissimilar patterns of statistical relationships among various dependent variables i.e. a particular and concise goal of analyzing different variables and similarly the other independent variables which effects them, even if the variables are incorrectly measured. While applying factor analysis following major questions are usually proposed:

1) “How many different factors are needed to explain the pattern of relationships among these variables?

2) What is the nature of those factors?

3) How well do the hypothesized factors explain the observed data?

4) How much purely random or unique variance does each observed variable include?”

Example of Factor-Analysis

Financial Institutions

Outsource2India is an Indian outsourcing solution providers. It generally provides the use of factor analysis by presenting themselves as financial institution in the home loans business. The customers have now come up with plenty of options with good credits, the technique of factor analysis would be obeying the variables related to the financial institution, a customer can choose for the loan. After the completion of the variable's list, factor analysis provides different significant factors i.e. a smaller list usually defines the better sample choice. After analyzing the financial institutional factors, the company then moves forward to market their products depending on the results.

Multi-dimensional scaling (MDS)

The multidimensional scaling (MDS) is a statistical technique commonly used in marketing and social sciences for ...