The overall objective of factor analysis is data summarization and data reduction. A central aim of factor analysis is the orderly simplification of a number of interrelated measures. Factor analysis describes the data using many fewer dimensions than original variables.
What is the purpose of factor analysis psych?
Applications in psychology Factor analysis is used to identify factors that explain a variety of results on different tests. For example, intelligence research found that people who get a high score on a test of verbal ability are also good on other tests that require verbal abilities.
What is factor analysis easy explanation?
Factor analysis is a way to take a mass of data and shrinking it to a smaller data set that is more manageable and more understandable. Factors are listed according to factor loadings, or how much variation in the data they can explain. The two types: exploratory and confirmatory.
How do you interpret a factor analysis in SPSS?
Initial Eigenvalues Total: Total variance. Initial Eigenvalues % of variance: The percent of variance attributable to each factor. Initial Eigenvalues Cumulative %: Cumulative variance of the factor when added to the previous factors. Extraction sums of Squared Loadings Total: Total variance after extraction.
How do you interpret factors in factor analysis?
Loadings close to -1 or 1 indicate that the factor strongly influences the variable. Loadings close to 0 indicate that the factor has a weak influence on the variable. Some variables may have high loadings on multiple factors. Unrotated factor loadings are often difficult to interpret.
How do you interpret a factor analysis?
Step 1: Determine the number of factors. If you do not know the number of factors to use, first perform the analysis using the principal components method of extraction, without specifying the number of factors. Step 2: Interpret the factors. Step 3: Check your data for problems.