SSRIC LogoRELG 4 Exercise

Exercise Using SPSS to Explore Conceptualization, Measurement, and Relationships Among Variables

Ed Nelson and Elizabeth Nelson, Department of Sociology
California State University, Fresno

RELG 4 Data

© The Authors, 1998; Last Modified 05 September 2001

Note to the instructor: The data set used in this exercise is RELG9800 which is a combination of the 1998 and 2000 General Social Surveys. (Some of the variables in the GSS have been recoded to make them easier to use and some new variables have been created.) This exercise uses RECODE to combine categories in existing variables, SELECT CASES to select out a subset of cases, and CROSSTABS to explore the relationships among 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 9.0 A Basic Tutorial by Richard Shaffer, Edward Nelson, Nan Chico, John Korey, Elizabeth Nelson and Jim Ross. To order this book, call McGraw-Hill at 1-800-338-3987. The ISBN is 0-07-241445-6 . There is an online version of the book at SPSS Text. You have permission to use this exercise and to revise it to fit your needs. Please send a copy of any revision to the authors.

Ed Nelson and Elizabeth Nelson
Department of Sociology, M/S SS107
California State University, Fresno
Fresno, CA 93740
Phone: 559-278-2275


Please contact the authors for additional information.

Goals of Exercise

The goal of this exercise is to think about a concept typically called religious fundamentalism and to consider how we might measure this concept using data from the General Social Survey. Once we have decided on a measure, then we will explore the relationship between this variable and various forms of religious behavior and opinions on various social issues.

Part I

You have probably heard some religions and individuals described as fundamentalist. Have you ever wondered what that meant? Keith Roberts, in his book Religion in Sociological Perspective (Wadsworth, 1995), says that fundamentalists insist "on the inerrancy of scripture and on a literal interpretation of the Bible." (page 370) The project directors for the General Social Survey created a variable called FUND. This variable classifies religions as fundamentalist, moderate, or liberal. In order to see which religions are classified as fundamentalist, run a crosstabulation with FUND as the independent variable and DENOM as the dependent variable. DENOM is a variable that tells you the Protestant denomination that Protestants belongs to.

What did you find out? You should have discovered that all the members of a particular denomination are placed in the same category of FUND. So a particular Protestant denomination is classified as fundamentalist or not. Every member of that denomination is placed into the same category. But that creates a problem. There is a lot of variety among people who belong to the same denomination. It would be nice to find a variable that takes this variation into account.

One of the questions in the General Social Survey (variable is BIBLE) asks respondents which of the following statements is closest to their feelings about the Bible.

1. "The Bible is the actual word of God and is to be taken literally word for word."

2. "The Bible is the inspired word of God but not everything in it should be taken literally, word for word."

3. "The Bible is an ancient book of fables, legends, history, and moral precepts recorded by men."

There is also a category for respondents who volunteer other answers.

This question seems to capture what Roberts says fundamentalism means. Those who say the Bible is the actual word of God and is to be taken literally word for word are clearly expressing a fundamentalist position. We could use this as another measure of fundamentalism. Letís recode BIBLE by combining the other category (value 4) with those who say the Bible is an ancient book of fables (value 3). There arenít many who volunteer another answer and this would reduce the number of categories and make our analysis simpler. Do this be recoding into a different variable. You could call this new variable BIBLE1 and recode 1 as 1, 2 as 2, 3 as 3, and then recode 4 as 3. This would keep the first two categories the same and combine categories three and four. Do the recoding and then run a frequency distribution for both BIBLE and BIBLE1 to make sure that you have done it correctly. Then you will want to assign value labels for the new variable, BIBLE1.

Part II

Now that we have found a measure of fundamentalism in our data set, letís see if there are any differences in religious behavior between fundamentalists and non-fundamentalists. First, letís look for variables that measure religious behavior. One of the questions asks respondents to estimate the strength of their religious affiliation. This variable in the GSS is called RELITEN. Respondents were also asked how often they attend religious services (ATTEND) and how often they pray (PRAY).

Before you start, run FREQUENCIES in SPSS for these three variables (RELITEN, ATTEND, PRAY). Letís recode all three of these variables as different variables.

The variable RELITEN records the respondentís self-reported strength of affiliation. The possible categories are strong (value 1), somewhat strong (2), not very strong (3), and no religion (4). Letís combine somewhat strong, not very strong, and no religion into one category and give that category a value of 2. Weíll recode this into a new variable and call it RELITEN1. Now we have two categories--strong (1) and not strong (2). (Hint: Be sure to recode into a different variable and not into the same variable.)

Now letís recode ATTEND into a new variable weíll call ATTEND1. Letís combine every week (value 7) and more than once a week (8) into one category and give this category a value of 1. Combine once a month (4), two to three times a month (5), and nearly every week (6) into another category and give this a value of 2. Finally, combine never (0), less than once a year (1), once a year (2), and several times a year (3) into another category and give this a value of 3. Now we have three categories--often (1), sometimes (2), and infrequently (3).

Finally, letís recode PRAY into a new variable called PRAY1. Combine several times a day (value 1) and once a day (2) into one category and give that a value of 1. Combine several times a week (3) and once a week (4) into another category and give that a value of 2. Combine less than once a week (5) and never (6) into another category and give that a value of 3. Now we have three categories--often (1), sometimes (2), and infrequently (3).

Now that you have recoded these variables, run FREQUENCIES in SPSS to get a frequency distribution for each of these three recoded variables. Compare these distributions to the distributions you ran before you started to see if you made any mistakes. If you did, you can just delete the new variable and start over. To delete a variable in SPSS, make sure you are in the data editor screen and click on the variable name at the top of each column. All your recoded variables will be at the far right of the screen. When you click on the variable name, the entire column should be highlighted. Press the delete key and it will disappear. Be careful. You donít want to delete the wrong variable.

Once you are sure that the variables have been recoded properly, add value labels for the recoded variables so the output will be easier to read.

Part III

Now that we have found some measures of religious behavior, letís see if there are any differences between fundamentalists and non-fundamentalists in terms of these variables. To do this we will have to run three crosstabulations with BIBLE1 as our independent variable and RELITTEN1, ATTEND1, and PRAY1 as dependent variables. Be sure to get the column percents and this time ask for Chi Square (a test of the null hypothesis that the two variables are unrelated) and Gamma (a measure of the strength of the relationship or association).

Write several paragraphs describing the relationship of BIBLE1 to each of these measures of religious behavior. How do fundamentalists differ from non-fundamentalists? Use the percents to help you describe the relationship. Does Chi Square let you reject the null hypothesis that the variables are statistically unrelated? What does Gamma tell about the strength of the relationship?

Part IV

Letís look in the data set for some measures of the respondentís opinion on social issues. You can click on Utilities in the menu bar of SPSS and then on Variables in the Utilitiesí menu to see a list of the variables in the data set. There are questions on divorce laws (DIVLAW), legalization of Marijuana (GRASS), gun laws (GUNLAW), homosexual sex relations (HOMOSEX), suicide (SUICIDE1, SUICIDE2, SUICIDE3, SUICIDE4), allowing incurable patients to die (LETDIE1), pornography laws (PORNLAW), sex before marriage (PREMARSX), sex education in the public schools (SEXEDUC), trust (TRUST), and others.

Choose one of these variables for your analysis. Select a variable on which you think fundamentalists and non-fundamentalists will disagree.

1. Write a hypothesis stating how you expect fundamentalists and non-fundamentalists to differ.

2. Write a paragraph or two that indicates why you think fundamentalists and non-fundamentalists will differ. In other words, write an argument in which your hypothesis is the conclusion to your argument.

3. Use SPSS to run the crosstabulation of BIBLE1 and your variable. Think about which is the independent and dependent variable. Remember to get the correct percentages. Use Chi Square and an appropriate measure of the strength of the relationship or association.

4. Write a paragraph interpreting the table that SPSS gave you and indicate whether the data support your hypothesis. Use the percents, Chi Square, and the measure of association to help you interpret the table.

Part V

Fundamentalism seems to be a concept that applies most directly to Christians. Letís see what would happen if we restricted our analysis to Christians only. To do this, click on Data on the menu bar in the Data Editor window. Then click on Select Cases. What you want to do is to select only those cases which are 1 (Protestant) or 2 (Catholic) on the variable, RELIG. This will select out the Protestants and Catholics for further analysis. Your instructor will show you how to do this.

Repeat the analysis you did in Parts III to IV and see if there are any differences when you restrict your analysis to Christians only.

When you are done, remember to click on Data on the menu bar in the Data Editor window and then on Select Cases and select All Cases and click on OK. This will remove the selection of Protestants and Catholics and allow you to continue any further analysis will all the cases.

Exercise Main Page