GENDER3G: Exercise Using SPSS to Explore Gender Differences on Social Issues

Author:   Ed Nelson
Department of Sociology M/S SS97
California State University, Fresno
Fresno, CA 93740

Note to the Instructor: The data set used in this exercise is gss14_subset_for_classes_GENDER_DIFFERENCES.sav which is a subset of the 2014 General Social Survey.  Some of the variables in the GSS have been recoded to make them easier to use and some new variables have been created.  The data have been weighted according to the instructions from the National Opinion Research Center.  This exercise uses FREQUENCIES to get frequency distributions, and CROSSTABS to explore the relationships between variables.  In CROSSTABS students are asked to use percentages, Chi Square, and an appropriate measure of association.  A good reference on using SPSS is SPSS for Windows Version 23.0 A Basic Tutorial by Linda Fiddler, John Korey, Edward Nelson (Editor), and Elizabeth Nelson.  The online version of the book is on the Social Science Research and Instructional Center's website.  You have permission to use this exercise and to revise it to fit your needs.  Please send a copy of any revision to the author. Included with this exercise (as separate files) are more detailed notes to the instructors, the SPSS syntax necessary to carry out the exercise (SPSS syntax file), and the SPSS output for the exercise (SPSS output file). These, of course, will need to be removed as you prepare the exercise for your students.  Please contact the author for additional information.

I’m attaching the following files.

Goals of Exercise

The goal of this exercise is to explore differences between men and women on the social issues of abortion, capital punishment, and gun control.  The exercise also gives you practice in using two SPSS commands – FREQUENCIES and CROSSTABS.

Part I—Social Issues

We’re going to use the General Social Survey (GSS) for this exercise.  The GSS is a national probability sample of adults in the United States conducted by the National Opinion Research Center.  For this exercise we’re going to use a subset of the 2014 GSS survey. Your instructor will tell you how to access this data set which is called gss14_subset_for_classes_GENDER_DIFFERENCES.sav.

In Exercises Gender1G and 2G we looked at gender differences in voting and discovered that females were more likely than males to vote for the Democrat candidate for president.  The Gallup Poll has tracked the gender gap for voting in presidential elections and their data show that females were more likely than males to vote for the Democrat candidate in all elections from 1952 to the present (see the Gallup Poll's website).

In this exercise we’re going to look at three social issues – abortion, capital punishment, and gun control.  Let’s start by getting frequency distributions for how people feel about these issues.

  • The GSS asked respondents whether they thought that it should be legal for a woman to obtain an abortion in seven scenarios:
    • A1_ABANY – for any reason,
    • A2_ABDEFECT – if there was a strong chance of a birth defect,
    • A3_ABHLTH – if the woman’s health was seriously endangered,
    • A4_ABNOMORE – if the woman was married and wanted no more children,
    • A5_ABPOOR – if the woman was low income and couldn’t afford more children,
    • A6_ABSINGLE – if the woman was not married, and
    • A7_ABRAPE – if the woman was pregnant as a result of rape.
  • Respondents were asked if they favored or opposed the death penalty for murder – C3_CAPPUN.
  • The GSS also asked if they favored or opposed gun permits – G1_GUNLAW[1].

Run FREQUENCIES in SPSS to get frequency distributions for all nine of these variables.  (See Frequencies, in Chapter 4 in the online SPSS book mentioned on page 1.)  Write a paragraph summarizing what you discovered about attitudes towards these issues.

Part II – Gender Differences for these Social Issues

Before we look at gender differences for these social issues let’s think about what we would expect to find.  A hypothesis states the relationship you expect to find between two variables.  For example, for abortion we might hypothesize that women would be more likely than men to think that abortion should be legal or we could hypothesize that men would be more likely than women to feel this way or we could suggest that there are no differences between men and women.  We would state our hypothesis before we looked at the data.

We would also want to explain why we think our hypothesis will be true.  In other words, we would write an argument for which the hypothesis is the conclusion to the argument.  If we thought that women were more likely than men to think abortion should be legal we might argue that women would want to have control over their bodies and therefore would be more likely to think that abortion should be legal.  But if we thought that women were less likely than men to think that abortion should be legal we might point to the fact that by every measure of religiosity women are more religious than men and those who are more religious tend to be more opposed to abortion.  Therefore women would be less likely to feel that abortion should be legal.

Now that you understand what a hypothesis and an argument is write two paragraphs that state your hypothesis and argument for the issues of capital punishment and gun control.  Be sure to indicate whether you think that women are more or less likely than men to favor or oppose capital punishment and gun control and why you think that is the case.

Part III – Determining the Gender Differences for Abortion, Capital Punishment, and Gun Control

Run CROSSTABS in SPSS to determine how men and women (D5_SEX) feel about these social issues.  (See Chapter 5, CROSSTABS, in the online SPSS book.)  Use all seven variables for abortion (i.e., A1_ABANY, A2_ABDEFECT, A3_ABHLTH, A4_ABNOMORE, A5_ABPOOR, A6_ABSINGLE, A7_ABRAPE), C3_CAPPUN for capital punishment, and G1_GUNLAW for gun control.  You’ll need to decide what you want to use as your independent variable and what you want to use as your dependent variable.  The dependent variable is what you are trying to explain and the independent variable is the variable that you think will help you explain the variation in your dependent variable.  Put the independent variable in the column and the dependent variable in the row of your table.  If you do this, you will always want to tell SPSS to compute the column percents.  Also tell SPSS to compute Chi Square and an appropriate measure of association.

Write a paragraph describing the relationship between gender and these nine variables that are our measures of how people feel about these three social issues.  Were males more or less likely than females to think that abortion should be legal, to favor capital punishment, and to favor gun permits?   Use the percents, Chi Square, and the measure of association to help you describe these relationships.  For abortion be aware that the gender differences might be different for the various measures of how people feel about abortion.  To help you organize your findings, there is a table at the end of this exercise where you can fill in the gender differences, the significance of Chi Square, and the value of Gamma.  We’ll define the gender gap as the percent for males minus the percent for females.

Part IV – Conclusions

Look back at the hypotheses and arguments you wrote in Part 1.  Do the gender differences support your hypotheses?  In the case of abortion, keep in mind that the results for some of the seven measures might support the hypothesis while the others might not support it.  What do the data suggest about your arguments?


Gender Gaps for Social Issues



Gender Gap

Chi Square


For any reason


Strong chance of birth defect


Woman’s health seriously endangered


Not married and wants no more children


Low income and can’t afford more children


Not married


Pregnant as a result of rape




Capital Punishment

Gender Gap

Chi Square


Favor death penalty for murder




Gun Control

Gender Gap

Chi Square


Favor gun permits





[1] Variable names are in all capitals.