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The objective for this week is to describe in more detail the relationship between different measures of religiosity. After you complete reading and doing Chapters 11, 13-15 in Babbie & Halley’s Adventures in social research, complete the following brief exercises. These questions assume you have already gone through the assigned chapters. Submit your work next week (October 27) at the beginning of the class session. You will need to use the GSS.SAV file supplied with your book and your GSS file in your P-drive. Please do not use the file in the K-drive folder.
Until this process is completed on
each machine we use, you will have to repeat this step on each new machine
you use that has not be reset.
First, compute a frequency distribution of PRAY, ATTEND, and POSTLIFE. Next, use the Transform à Compute command and in the upper left window, type in the new variable name "RELBELIF." The variable now exists, but it does not yet have variability (or data). To begin identifying the values of this new variable, enter 0 in the big, upper left numeric expression window and click "OK". We have just assigned everyone a baseline value of zero. (If already confused, refer to Chapter 9, p. 78 for more details on the process of entering data). Select Transform à Compute again, and click the "reset" button at the bottom of this "page." Type RELBELIF into the upper left target field again, and in the upper right type RELBELIF+1 Click the "If" button in the middle of this "page" and notice a new page. Using this page we set the conditions for who will be recoded from a zero to a one. First toggle "Include if case satisfies condition" in the upper right, otherwise the screen will remain gray and you will not be able to select a variable. Select POSTLIFE from the variable list, and after it enters the rectangluar window add the condition = 1 then click "continue" and when the screen changes, click "OK". The program will query "Change the existing variable?" which is exactly what you want to do, so click "OK" again. You have now created RELBELIEF with two values – zero and one. We need to continue. Again select Transform à Compute and click "reset." Again type RELBELIEF into the target field and REBELIEF+1 into the upper right window. Next, again click the "If" button, select "PRAY" from the variable list, and after it enters the window add the condition <3 then click "OK" and again "OK". The condition <3 for PRAY specified that people who had a code of 1 or 2 (prayed several times a day or prayed once a day) be added to the RELBELIEF index. We now have possible scores ranging from zero to 2. One more time, select Transform à Compute and click "reset." Type RELBELIEF into the targer field and RELBELIEF+1 into the other window. Click "If" and select "ATTEND" from the variable list, and set its condition as > 5. [This translates into people who scored 6, 7, 8. The attend nearly every week, or every week, or more often.] You now have a composite index that has a possible range from zero to 3. Compute a frequency distribution and print a copy of the table. Validate your index. Compute a correlation
between RELBELIEF, PREMARSX, and HOMOSEX. What are the correlations coeffienents?
Are the positive or negative? How do you interpret them (see pp. 229-230
to see the way the two sex variables were coded)?
Drawing from the crosstab tables, what
______% of the Catholic respondents rarely or never pray, and ________%
of the Protestants pray several times a day. Do Catholic, Protestant, and
Jews participate in their religion equally? Who is more involved in their
religion, as determined by their extrinsic religiosity? Now, who is more
involved as defined by their intrinsic religiosity?
Develop a new variable "AGECAT" by using the Transform à RECODE command. Recode AGE into AGECAT (using the "recode into different variable" toggle) and create five categories – under 25, 25-40, 41-55, 55-70, 71+. Compute a frequency distribution of this variable. Save your files (and thus save your recoded work). Develop another variable "CHATT" using the Transform à Recode command. Recode ATTEND into CHATT with four categories – never (0), rarely (1,2=1), monthly (3,4,5=2), and at least weekly (6,7,8=3). Compute a frequency distribution of this variable. Save your files (and thus save your recoded work). Develop another variable "PRAY2" by
recoding pray into three categories – rarely (5,6=1), occasionally (3,4=2),
often (1,2=3). Set "all other values" to SYSMIS. Compute a frequency distribution
of PRAY and PRAY2. Save your files (and thus save your recoded work).
What evidence do you have to support the deprivation theory of religiosity? First, is each observed relationship between RELITEN and sex, age, and class statistically significant? (You answer this by reviewing the significance of the chi-square statistic; is it less than .05?) Second, how strong is each observed relationship? (You assess strength of relationship with a measure of association, and I asked you to select the Cramer’s V statistic). Strength of affiliation
c 2(Chi
square) Cramer’s V
by age by class You are assessing what variable? (Look at the variable label and then look at the value labels to see how the variable was coded.) Are the relationships between this variable and sex, age, and class chance relationships or reliable relationships (recall, the chi square statistic determines the significance of the relationship, and for chance relationships the chi square is greater than .05)? According to the Cramer’s V, are the observed relationships weak, moderate, or strong? Strength of affiliation c 2(Chi square) Cramer’s V by sex by age by class |