We have already discussed about factor analysis in previous article (Factor Analysis using SPSS), and how it should be conducted using SPSS. In this article we will be discussing about how output of Factor analysis can be interpreted.
Factor analysis is used to find factors among observed variables. In other words, if your data contains many variables, you can use factor analysis to reduce the number of variables.
If you want to test whether the % of people who report themselves to be very happy has changed during the time that the test has been conducted. A special case of the chi square test for independence is the test.
A chi square (X2) statistic is used to investigate whether distributions of categorical variables differ from one another. Categorical variables like; gender of sample population which could be either male or female.
A paired sample t-test is used to determine whether there is a significant difference between the average values of the same measurement made under two different conditions.
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When using this statistical test, you are testing the null hypothesis that 2 population means (average) are equal. The alternative hypothesis is that they are not equal.