Day 8 - Group B_Factor Analysis

Understanding of Factor Analsis:

Factor analysis aims to describe a large number of variables or questions by only using a reduced set of underlying variables, called factors. It explains a pattern of similarity between observed variables. Questions which belong to one factor are highly correlated with each other. Unlike cluster analysis, which classifies respondents, factor analysis groups variables.

There are two types of factor analysis: exploratory and confirmatory. Exploratory factor analysis is driven by the data, i.e. the data determines the factors. Confirmatory factor analysis, used in structural equation modelling, tests and confirms hypotheses.
Factor analysis is often used in customer satisfaction studies to identify underlying service dimensions, and in profiling studies to determine core attitudes. For example, as part of a national survey on political opinions, respondents may answer three separate questions regarding environmental policy, reflecting issues at the local, regional and national level. Factor analysis can be used to establish whether the three measures do, in fact, measure the same thing.
It can also prove to be useful when a lengthy questionnaire needs to be shortened, but still retain key questions. Factor analysis will indicate which questions can be omitted without losing too much information.

 

 

The best way of understanding Factor Analysis is through a video.

 

Also, a proper descrption about Factor Anaylsis can be understood by following the manual attached below:

Factor Analysis - a Better understanding

Being a Marketing student, I would like to share how important is Factor Analysis for a Marketer.

Factor analysis helps marketers determine how changing one thing affects sales and more. In essence, marketing factor analysis is changing one marketing variable to see what affect, if any, the change has on the outcome. The change in sales also affects the bottom line of the company, so factor analysis in marketing helps companies determine which marketing efforts it should pursue, which efforts need work and which marketing efforts may meet the cutting room floor.

 

The significance of Factor Analysis in Marketing: According to BNet, factor analysis in marketing requires an evaluation of how changing one marketing point, such as price, changes the sales of the product. In order to measure how the factor changes the sales, it requires that only one marketing variable is changed at a time in order to measure the relationship between the variables and the outcome. In marketing, changing one variable can be significant because it may cause an increase or decrease the sales of the product.

 

Variables in Factor Analysis: An infinite number of marketing variables can exist, which is why it is necessary to alter only one at a time. Marketing variables include the product, the product packaging, the size of the product and the color of the product. The price, distribution channels and marketing strategies may also be variables of the product that can be changed to see how the change makes a difference in the sales of the product.

 

What customers want: Factor analysis in marketing is important because it reflects the perception of the buyer of the product. By testing variables, it is possible for marketing professionals to determine what is important to the customers of the product. For example, if a product is only available in black and the sales reach $150,000 in one year, but when the company adds color options of red, blue and silver, and sales reach $300,000, then the company can conclude through factor analysis that color options are important to the customers of the product. Ultimately, it is imperative to use factor analysis in marketing to create the ideal product for customers, which in turn, increases the sales of the product.

Conducting Factor analysis: Generally, companies test variables with factor analysis in marketing using tools such as focus groups and surveys. Since making changes to the product itself in order to test variables can be expensive, surveys and focus groups allows companies to gather pertinent information without increasing the cost to manufacture the product. Focus groups and surveys allow companies to gather perceptual information from current and potential customers of the product. This information is important because it allows the company to see the product from the vantage point of the customers and determine which factors in marketing are the most important to the customers. For example, a focus group may see four different package versions of a product and then ask the focus group participants to choose which package they like best and explain why. Companies can use this information to alter product packaging to attract more customers and sell more products.

Disadvantages of Factor Analysis:

1. Factor analysis can be only as good as the data allows. In psychology, where researchers often have to rely on less valid and reliable measures such as self-reports, this can be problematic.
2. Interpreting factor analysis is based on using a "heuristic", which is a solution that is "convenient even if not absolutely true"  
3. More than one interpretation can be made of the same data factored the same way, and factor analysis cannot identify causality.

Thumb rules for Scree Plot:

1. One rule is to consider only those with eigenvalues over 1.
2. Plot all the eigenvalues in their decreasing order.

The Scree plot looks like the side of a mountain, and "scree" refers to the debris fallen from a mountain and lying at its base. So the sree test proposes to stop analysis at the point the mountain ends and the debris (error) begins.

The best way of upderstanding the Scree plot is through the following document. The example is about Measuring Police attitudes towards people with mental illness.

Measuring Police attitudes towards people with mental illness 

BTW, Scree means 

1. Loose rock debris covering a slope.
2. A slope of loose rock debris at the base of a steep incline or cliff.

Factor analysis Rotation method:

Allows you to select the method of factor rotation. Available methods are varimax, direct oblimin, quartimax, equamax, or promax.

1. Varimax Method: An orthogonal rotation method that minimizes the number of variables that have high loadings on each factor. This method simplifies the interpretation of the factors.
2. Direct Oblimin Method: A method for oblique (nonorthogonal) rotation. When delta equals 0 (the default), solutions are most oblique. As delta becomes more negative, the factors become less oblique. To override the default delta of 0, enter a number less than or equal to 0.8.
3. Quartimax Method: A rotation method that minimizes the number of factors needed to explain each variable. This method simplifies the interpretation of the observed variables.
4. Equamax Method: A rotation method that is a combination of the varimax method, which simplifies the factors, and the quartimax method, which simplifies the variables. The number of variables that load highly on a factor and the number of factors needed to explain a variable are minimized.
5. Promax Rotation: An oblique rotation, which allows factors to be correlated. This rotation can be calculated more quickly than a direct oblimin rotation, so it is useful for large datasets.

 

Scatter Plot:

 

A scatter plot or scattergraph is a type of mathematical diagram using Cartesian coordinates to display values for two variables for a set of data.
The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis. This kind of plot is also called a scatter chart, scattergram, scatter diagram or scatter graph.
 

 

* - In factor analysis, we need to look at the Original values. Thus it will be easy for us to understand the scatter plot.  

Submitte by - 

Kaustubh A. Bhake

Group B