Chapter 5 Exercises Using Data from 1995 Field Poll on Women's Issues

© The Authors, 1998; Last Modified 15 August 1998
In the previous chapter we discussed data analysis. In this chapter you will have an opportunity to analyze data. The exercises in this chapter start at a fairly simple level and become more complex. The final exercise asks you to define your own problem and carry out the analysis. (Your instructor may choose to supplement these exercises with some of his or her own.) You will be using your computer facilities to do these exercises, but there is no assumption that you know anything about computers before you start. Every effort has been made to minimize what you will have to learn about computers. Your instructor will provide you with the necessary information.

EXERCISE ONE

One of the questions in the data set asks respondents whether there are "more advantages in being a man, more advantages in being a woman, or ... no more advantages in being one or the other." We want to find out some of the factors that are related to this opinion. Specifically, we want to know if men and women differ in their opinions, and whether education is related to how one feels about this matter.

Question 1. Find this question in the codebook (see Appendix A). Locate the variable name for this question. This is the name the computer recognizes. You will have to use this name when asking the computer to do something for you. What is the variable name?

Question 2. The codebook gives both the frequency distribution and the percentage distribution for this question. What percent feel that there is more of an advantage in being a man? What percent feel there is more of an advantage in being a woman? What percent think it doesn't make any difference if one is a man or a woman? Show how these percentages were calculated (i.e., do the simple arithmetic to compute this percentage).

Question 3. We would like to know if men and women hold different opinions? To answer this, we must crosstabulate sex (V34) and advantages in being a man or a woman (V1). We're interested in comparing the opinions of men and women. So sex (V34) is the independent variable and advantages in being a man or a woman (V1) is the dependent variable. (You probably will want to review Chapter Three on independent and dependent variables.) Be sure to ask for the appropriate percentages (either the row or the column percents) and chi square. Ask the computer to give you the appropriate measure of association (either Cramer's V or Gamma). After you get the table, write a short paragraph interpreting your results. Be sure to refer to the percentages from the table, chi square, and the measure of association. Remember that you are trying to determine if men and women differ in their opinions, and, if so, how they differ.

Question 4. Would people with more education be more or less likely to see advantages to being a man? You will want to crosstabulate education (V24) and advantages in being a man or a woman (V1). First, let's recode education by dividing it into three categories--those who have a high school degree or trade school or less, those with some college but no college degree, and those who have a college degree (bachelor's, master's, or post-master's). Now crosstabulate the recoded education variable (V24) and advantages in being a man or a woman (V1). Be sure to get the appropriate percentages, chi square, and the appropriate measure of association. Write a short paragraph interpreting your results. Use all the statistics (i.e., percentages, chi square, measure of association) in your answer. Remember that the question is whether there is a relationship between education and whether one thinks there is an advantage in being a man or a woman, and, if so, what the relationship is.

Question 5. In the previous questions, we considered sex and education separately. In other words, we first crosstabulated sex and advantages and then crosstabulated education and advantages, producing two tables, each with two variables. Now we want to crosstabulate advantages and sex using education as the control variable. In other words, we want to compare the opinions of men and women holding education constant (review Chapter Three). Use the recoded version of education that you created for question four. After you have obtained the tables, start by looking at the relationship between sex and advantages for those with a high school degree or less. Do men and women with a high school or less education differ in their opinions? Now look at those with some college and then finally those with a college degree. Do these men and women differ in their opinions? Be sure to use the percentages, chi square, and the measure of association to help you answer these questions. Write a paragraph or two summarizing your findings.

Question 6. This time let's crosstabulate advantages and education using sex as the control variable. In other words, we want to compare the opinions of those with different educational levels holding sex constant. Use the recoded version of education that you used for questions four and five. After you have obtained the tables, start by looking at the relationship between education and advantages for the males. Is there a relationship? What kind of relationship exists (i.e., are those with more education more or less likely to think that there is an advantage in being a man)? Now look at the females. Is there a relationship? Write a paragraph or two summarizing your findings. Be sure to use the statistics to help you. Why do you think these findings occurred? In other words, what do you think accounts for these relationships?

EXERCISE TWO

The Field Poll included two very interesting questions about housework. One of the questions asks who should clean the house when both the husband and the wife work full time outside the home; the other asks who actually does most of the housework in the home. These questions open a number of intriguing opportunities for analysis.

Question 1. Let's start by looking at the percentage distributions. Find these two questions in the codebook and locate the variable names. Who do most respondents think should clean the house when both partners work full time? What percent of the respondents gave this answer? Who do the respondents think is actually doing the housework in their homes? Write a complete sentence summarizing the answers of the respondents in the sample. Use example percents to illustrate your description.

Question 2. It would be interesting to know how the married females with spouses who work full time feel about housework. The computer can help us by selecting only the married females who have spouses who work full time. This means you will have to tell the computer to select out the married (value 1 on V19) females (value 2 on V34) whose spouse works full time (value 1 on V20). (Your instructor will show you how to do this.) What percent of these married females think that both partners should share the housework equally when both partners work? What percent of these married females feel that the housework is being shared equally in their homes? (Hint: First, you will have to select out the married females with spouses who work full time. Then, you will have to ask for frequency distributions for the two questions dealing with housework.) Write a complete sentence summarizing these results.

Question 3. What about the married women who work full time themselves? Perhaps housework is shared more equally in the homes of these women than in the homes of the married women who don't work full time. To simplify this, have the computer recode the respondent's work status (V18) to separate those working full time from all others. Do this by combining part-time, temporarily unemployed, and not employed into one category. This will leave two categories -- employed full time and not employed full time. Obtain a frequency distribution for this recoded variable for these married females with spouses who work full time. What percent of these married females worked full time?

Question 4. By now it is clear that we want to compare the married women who work full time with the married women who don't and find out if housework is more likely to be shared in the homes of the married women who work full time than in the homes of the married women who don't work full time. Before you start, we had better go through the steps involved. First, select out the married females with spouses who work full time. Second, make sure that you have recoded employment status (V18). Third, crosstabulate who actually cleans the house (V3) and the recoded employment status (V18). We're really interested in comparing who does the housework in families in which women work full time and in families in which women do not work full time. We suspect that employment status influences who they think should do the housework. So employment status (V18) is the independent variable and who actually cleans the house (V3) is the dependent variable. (You probably will want to review Chapter Three on independent and dependent variables.) Fourth, be sure to ask the computer to give you the appropriate percentages, chi square, and the appropriate measure of association. After you get the table, write a short paragraph interpreting your table using the percentages, chi square, and the measure of association from your computer output. Summarize the relationship in words. Are the married women who work full time more or less likely than the married women who don't work full time to say that housework is shared equally in their

EXERCISE THREE

Another question asks respondents if they "favor or oppose efforts to strengthen and change women's status in society today." As in exercise one, we want to find out how some of the factors are related to one's opinion. We will focus on the relationship of sex, education, and age to opinions regarding women's status.

Question 1. Find this question in the codebook and locate the variable name. What percent favor efforts to strengthen and change women's status? What percent oppose such efforts? How many respondents had no opinion? What percent is this of the total number of respondents in the sample?

Question 2. Do men and women differ in their opinion? What two variables do we have to crosstabulate to answer this question? Be sure to obtain the percentages, chi square, and the appropriate measure of association. Write a short paragraph interpreting your table, using the statistics you obtained.

Question 3. Is education related to whether one favors or opposes efforts to strengthen or change women's status? Before you obtain the crosstabulation, be sure to recode education by dividing it into three categories--those who have a high school degree or trade school or less, those with some college but no college degree, and those who have a college degree. Obtain the crosstabulation you need to answer this question, along with the appropriate statistics. Write a short paragraph interpreting your table, using the statistics you obtained.

Question 4. For the rest of this exercise we want to consider only those respondents who work full time. You will have to tell the computer to select out these respondents. Do men and women who work full time differ in their opinions? Obtain the appropriate crosstabulation and statistics. Compare your results here with those in question two. Are they similar or different? Write a short paragraph interpreting your table and comparing it to the table from question two. Be sure to use the appropriate statistics to help you interpret these tables.

Question 5. For this question you should compare the opinions of men and women who work full time controlling for education. Remember to first select out those who work full time. Then obtain the appropriate three-variable table, along with the statistics. Has education affected the relationship between sex and opinion regarding women's status? Compare the partial tables obtained in this question with the two-variable table from question four. Write a short paragraph interpreting these results.

Question 6. There is a problem with the crosstabulations you obtained in question 5. Notice that the expected frequencies are less than five and that some of these expected frequencies are quite small. Chi square assumes that these expected frequencies are five or larger. Statisticians tell us that as long as 80 percent of the expected frequencies are five or larger and no single expected frequency is very small, we don't have to worry. However, in this case some of the expected frequencies are quite small. (You will want to review the section in Chapter Three on chi square.) We can solve this problem by recoding V2. How are we going to do this? If we combine favor strongly and favor somewhat we will have over 80 percent of the cases in this one category. It might be better to leave favor strongly as one category and combine favor somewhat, oppose somewhat, and oppose strongly as a second category. This would give us those who are strongly in favor of efforts to strengthen women's status in one category and all those less committed in another category. Recode V2 in this manner and repeat the analysis in question 5. Notice that the expected frequencies are larger now. You no longer violate one of the assumptions for chi square.

EXERCISE FOUR

1. Choose one of the questions about women's status and roles (V5 to V17) as a dependent variable. What is the variable name? Using the information in the codebook, write a sentence describing the responses to that question.
2. What variables do you think might be related to your dependent variable? Write down the ways in which these variables (i.e., your independent variables) might be related to the dependent variable. Be sure to explain the rationale underlying each hypothesis. (Review the discussion of hypotheses in Chapter Three.) In other words, explain why you think this hypothesis should be true.

3. For example, you might think that age would be related to the dependent variable such that, as age increases, your dependent variable decreases. Explain why age should be related to your dependent variable in this manner. Include at least three hypotheses.

One hypothesis should consider the relationship between sex and your dependent variable. (Would you expect men and women to be similar or different? Why? The rationale for your hypothesis should be organized as an argument leading us to conclude that your hypothesis is plausible.)

A second hypothesis should consider the relationship between your dependent variable and another social-status variable (e.g., age, race, education).

A third hypothesis should consider the relationship between one of the opinion variables (e.g., favor or oppose efforts to strengthen or change women's status) or behavior variables (e.g., who cleans house when both spouses work) and the dependent variable. You may consider more than three hypotheses that can be tested with these data.

4. Obtain the two-variable tables needed to check on your hypotheses. One crosstab should consider possible sex differences. The other tables should include one other social-status characteristic from the background data (V18 to V33) and one opinion or behavior variable (V1 to V17) as independent variables. Present these in the form of individual tables with a short written summary of the results of each table that links it back to the hypotheses considered.
5. Then choose one of your two-variable crosstabs and explore the relationship (or lack of relationship) more fully using another variable as a control. For example, you might want to consider the relationship between sex and your dependent variable controlling for such variables as age, income, or education. Restate your hypothesis as clearly as possible. Indicate why you selected this control variable. Present the three-variable table with a written summary that considers this hypothesis.
6. Write a brief summary of your findings. Be sure to discuss your hypotheses and whether the data support the hypotheses. What were the most important findings in your analysis?

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