Volu m e I - Purdue University Calumet

Totals
600
500
400
300
200
100
0
47.9%
30.3%
21.8%
Total
Respondents
respondents that respond as having an
increasing tolerance gradually decreases. The
same reaction can be seen across the board in
Tolerance
each level of service attendance.
From the number of respondents
that were surveyed, a total of 47.9% responded as having a low tolerance level. Subsequently, there were
30.3% who considered them selves to have a medium tolerance level, while the remaining 21.8% represent
the total of those who ranked within the high tolerance levels. The correlation between the variables is
much easier to interpret in the bar graph to the left. Here it is evident that the tolerance levels of
respondent are increasing as religious attendance does the same.
Working with my two variables that were later recoded into ordinal variables, I found it
relevant to run a Gamma test to determine the measure of association between the pair. The purpose of
such a test is to show if the relationship that exists between my dependent and independent variable is
worthy enough to mention in any research. On a scale of -1.00 to +1.00, the farther from zero on either
side of the spectrum, the stronger the relationship. By testing the relationship, I had found that relationship
between religious service attendance and political tolerance to gay rights exhibit relationship strength
of .220. Based on general guidelines that are used to categorize the different levels of association, I found
that the correlation is considered moderate and worth noting in further research.
Symmetric Measures
Value Asymp. Std. Error a Approx. T b Approx. Sig.
Ordinal by Ordinal Gamma .220 .041 5.313 .000
N of Valid Cases 1142
Accompanying my cross tabulation and Gamma assessment is the Chi-Square test. According
to Babbie, Halley, and Zaino’s Adventures in Social Research, a Chi-Square is a “test of statistical significance
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