Correlation Table

MAN 6316: HRM Metrics

Individual Analysis Project SPSS Correlation Output: Fall 2014

Individual Analysis Project: SPSS Correlation Output

This document contains the output that you will need to complete “Step 2” of the Analysis Project:

The results from the SPSS correlation analysis of the dataset are provided below. SPSS is a powerful software tool, and is

often used by consultants and analysts to conduct advanced statistical data analysis. The results below are in their “rough

form,” just as they would be seen after the analysis was conducted in SPSS. As you can see, this table looks quite different

from the correlation table that we worked in for In-Class Assignment #2. Using the in-class assignment as a guide, please

create your own, more stream-lined correlation table using the information from the table below.

To assist you in interpreting the above correlation output, here is some helpful information about the terms used in the table.

Pearson correlation: This is the correlation between the two relationships (“Pearson” simply refers Karl Pearson, who is the

person who developed the method of correlation). For instance, the value .151 refers to the correlation between Pay

Satisfaction and Gender.

Sig. (2-tailed): This refers to the actual significance level of the correlation. This number is more generally what researchers

would call the “p-value.” For instance, the p-value for the Pay Satisfaction and Gender correlation is .023. Because this p-

value of .023 is less than .05 (the arbitrary threshold that indicates statistical significance), the correlation between Pay

Satisfaction and Gender is considered statistically significant. The statistical significance of this correlation is further

indicated by the star (*) that appears next to it (e.g., .151*). Rather than reporting the actual p-values of a correlation,

researchers will often simply flag their significant correlations with asterisks/stars (*). This is an easy way for researchers to

show that which results are statistically significant.

N: This number refers to the number of cases used in the analysis. The term “case” refers to the individuals surveyed or polled

in a study. In this instance, data from 225 individuals was used in the analysis (notice in the Excel dataset that there are 225

rows of actual data), thus we see the number 225 in the correlation output. Letting your audience know how many cases were

used in an analysis is important, as it can influence the statistical and practical significance of your findings.