Methods for Social Researchers in Developing Countries


Introduction

Bivariate
analysis:
nominal
variables

Bivariate
analysis:
ordinal
variables

Statistical
tests of
association

Aids
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Obtaining two-way frequencies

For this research, imagine that we asked 150 adult men and 150 adult women whether they were "in favor of" or "opposed to" women having the same rights as men. After getting these data, we would first conduct univariate analyses based the frequency distributions for each variable. Then, we would be ready to proceed to testing the relationship between the two variables by looking at their joint frequency distribution. To start, we need frequencies for of the following combinations:

Females in favor of
Females opposed to
Males in favor of
Males opposed to

To find these four frequencies, we would first separate respondents by gender, putting all questionnaires for females in one pile and those for males in another pile. Next, we would divide each of the gender piles into two additional piles, putting all those who answered in favor of and those who answered opposed to into separate piles. Figure 18.1 shows this process. The numbers at the bottom of the figure are the two-way frequencies for the cross classification based on gender and expression of attitudes toward gender equality



Figure 18.1 Flowchart for obtaining frequencies for a bivariate analysis

With these frequencies, we can find the percentages of females and males who gave favorable and unfavorable responses.

The percentage of females who gave favorable responses is 98/150 = 65%.
The percentage of females who gave unfavorable responses is 52/150 = 35%
The percentage of males who gave favorable views is 63/150 = 42%.
The percentage of males who gave unfavorable views is 87/150 =58%
The next step is to put these percentages into a properly constructed bivariate table.

Constructing a bivariate table

The percentages derived from the two-way sorting are shown in Table 18.1. Each percentage is shown in terms of both variables. This kind of table is also known as a cross classification or contingency table because the two variables are crossed with one another in the form of columns and rows of a table. It is customary to show the independent variable in the columns and the dependent variable in the rows of the table. In Table 18.1, gender, therefore, is shown in the columns and the two attitude views make up the rows of the table. The frequency of 98 and the corresponding 65% for females with favorable views are placed in the cell formed by the intersection of the column labeled female and row labeled "in favor of." The frequencies and percentages for the other three combinations are placed in their proper cells as well. In addition, the column to the right shows the totals for each attitude response for both females and males. The totals across the bottom show the totals for each gender.

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