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| Words: 1329 | Submitted: 24-Jan-2012
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Descriptionuses of factor analysis
Factor analysis is used to find latent variables or factors among observed variables. In other words, if your data contains many variables, you can use factor analysis to reduce the number of variables. Factor analysis groups variables with similar characteristics together. With factor analysis you can produce a small number of factors from a large number of variables which is capable of explaining the observed variance in the larger number of variables. The reduced factors can also be used for further analysis.
There are three stages in factor analysis:
First, a correlation matrix is generated for all the variables. A correlation matrix is a rectangular array of the correlation coefficients of the variables with each other.
Second, factors are extracted from the correlation matrix based on the correlation coefficients of the variables.
Third, the factors are rotated in order to maximize the relationship between the variables and some of the factors.
You may be interested to investigate the reasons why customers buy a product such as a particular brand of soft drink (e.g. coca cola). Several variables were identified which influence customer to buy coca cola. Some of the variables identified as being influential include cost of product, quality of product, availability of product, quantity of product, respectability of product, prestige attached to product,experience with product, and popularity of product. From this, you designed a questionnaire to solicit customers' view on a seven point scale, where 1 = not important and 7 = very important. The results from your questionnaire are show on the table below. Only the first twelve respondents (cases) are used in this example.
Table 1: Customer survey
Preparing the Data set
Prepare and enter the data into SPSS Data Editor window. If you do not know how to create SPSS data set see Getting Started with SPSS for Windows. Define the eight variables cost, quality, avabity, quantity, respect, prestige, experie, popula, and use the Variable Labels procedure to provide fuller labels cost of product, quality of product, availability of product, respectability of product, and so on to the variables names. The completed data set look like the one shown above in Table 1.
Running the Factor Analysis Procedure
From the menu bar select Statistics and choose Data Reduction and then click onFactor. The Factor Analysis dialogue box will be loaded on the screen. Click on the first variables on the list and drag down to highlight all the variables. Click on the arrow (>) to transfer them to the Variables box. The completed dialogue box should look like the one shown below.
The Factor Analysis dialogue box
All we need to do now is to select some options and run the procedure.
Click on the Descriptives button and its dialogue box will be loaded on the screen. Within this dialogue box select the following check boxes Coefficients,Determinant, KMO and Bartlett's test of sphericity, and Reproduced. Click onContinue to return to the Factor Analysis dialogue box. The Factor Analysis: Descriptives dialogue box should be completed as shown below.
The Factor Analysis: ...
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