Correlation is a statistical measure that helps in determining the extent of the relationship between two or more variables or factors. For example, growth in crime is positively related to growth in the sale of guns. Growth in obesity is positively correlated to growth in consumption of junk food. However, growth in environmental degradation is […]
The normal linear regression analysis and the ANOVA test are only able to take one dependent variable at a time. So one cannot measure the true effect if there are multiple dependent variables. In such cases multivariate analysis can be used.
It measures the correlations between two or more numeric variables. There are two types of correlations; bivariate and partial correlations. While Bivariate Correlations are computed using Pearson/Spearman Correlation Coefficient wherein it gives the measure of correlations between variables or rank orders.
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.
In my previous article “Introducing Data” we discussed about importing files and creation of data sheet in SPSS. Moving further, in this article I will be discussing about the most basic technique which can be applied within SPSS i.e. Frequency Testing.