Factor Analysis
Factor Analysis
Introduction
Basic Concept of Factor Analysis
Factor analysis is a statistical approach to reduce a large set of variables that are mostly correlated to each other to a small set of variables or factors. It is also used to explain the variables in the common underlying factors. (Hair et al, 1998) Malhotra, 2006 mentioned that factor analysis is also an interdependence technique that both dependent and independent variables are examined without making distinction between them
Conducting Factor Analysis
1. Formulate the problem
In this research, researcher’s objective is to determine the factors that influence customers’ satisfaction with their internet service provider in Malaysia such as Streamyx, Digi Broadband, Maxis Broadband, P1 and others (Malaysia Central, 2011). Mall intercept was used to interview a total of 30 respondents at Midvalley Megamall. Questionnaires were distributed and respondents are required to show their degree of agreement with the statements below whereby means very strongly disagree and means very strongly agrees:
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Figure 1.1: Input in SPSS 2. Is the data appropriate?
a) The correlation matrix
Base on the data above, the correlation matrix was run to examine if the factor analysis is appropriate. Variables opt to be inter-related in order to be suitable to conduct a factor analysis. In other words, if all the variables have nothing in common, they can’t be analyzed into common factor. Hair et al, 1998 indicates that rule of thumb for factor analysis is a considerable correlation of 0.3. Field, 2009 has emphasized that if there is any value greater then 0.9, the variables may be omitted. According to the result, V3 (quality support), V5 (sincere interest in problem solving), V6 (prompt service), V7 (willingness to help), V8 (politeness) and V9 (knowledgeable) have high correlations about more than 50% (as highlighted in yellow) All the 5 variables may be inter-related
Introduction
Basic Concept of Factor Analysis
Factor analysis is a statistical approach to reduce a large set of variables that are mostly correlated to each other to a small set of variables or factors. It is also used to explain the variables in the common underlying factors. (Hair et al, 1998) Malhotra, 2006 mentioned that factor analysis is also an interdependence technique that both dependent and independent variables are examined without making distinction between them
Conducting Factor Analysis
1. Formulate the problem
In this research, researcher’s objective is to determine the factors that influence customers’ satisfaction with their internet service provider in Malaysia such as Streamyx, Digi Broadband, Maxis Broadband, P1 and others (Malaysia Central, 2011). Mall intercept was used to interview a total of 30 respondents at Midvalley Megamall. Questionnaires were distributed and respondents are required to show their degree of agreement with the statements below whereby means very strongly disagree and means very strongly agrees:
[pic]
[pic]
Figure 1.1: Input in SPSS 2. Is the data appropriate?
a) The correlation matrix
Base on the data above, the correlation matrix was run to examine if the factor analysis is appropriate. Variables opt to be inter-related in order to be suitable to conduct a factor analysis. In other words, if all the variables have nothing in common, they can’t be analyzed into common factor. Hair et al, 1998 indicates that rule of thumb for factor analysis is a considerable correlation of 0.3. Field, 2009 has emphasized that if there is any value greater then 0.9, the variables may be omitted. According to the result, V3 (quality support), V5 (sincere interest in problem solving), V6 (prompt service), V7 (willingness to help), V8 (politeness) and V9 (knowledgeable) have high correlations about more than 50% (as highlighted in yellow) All the 5 variables may be inter-related