Transcription of Interpreting SPSS Correlation Output
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Interpreting SPSS Correlation Output
Interpreting SPSS Correlation Output Correlations estimate the strength of the linear relationship between two (and only two) variables. Correlation coefficients range from (a perfect negative Correlation ) to positive (a perfect positive Correlation ). The closer Correlation coefficients get to or , the stronger the Correlation . The closer a Correlation coefficient gets to zero, the weaker the Correlation is between the two variables. ordinal or ratio data (or a combination) must be used. The types of correlations we study do not use nominal data. SPSS permits calculation of many correlations at a time and presents the results in a Correlation matrix.. A sample Correlation matrix is given below. The variables are: Optimism: Compared to now, I expect that my family will be better off financially a year from now. Life Satisfaction: Overall, life is good for me and my family right now. Entrepreneurial Interest:: I am interested in starting a business or investing in a business in the next six months.
The dependent (Y) variable is always ordinal or ratio data while the independent (X) variable is always nominal data (or other data that’s converted to be nominal). With ANOVA, the independent variable can have as many levels as desired. A sample of SPSS ANOVA output is below and on the following page. The variables in this example are:
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