1. Define the values 0, 8, and 9 as "missing" for AFFRMACT. Then, recode AFFRMACT as follows to create the new variable AFFREC. When you have done that, be sure to set the decimal places for AFFREC to 0 and add value labels. Old Values New Values Labels 1 to 2 1 Support 3 to 4 Oppose System- or user-missing System-missing Run crosstabs listing RACE and SEX as the independent variables and AFFREC as the dependent variable. Request column percentages and chi-square. Then, answer Questions 2 through 6. 2. Record the percentage of respondents who said they "Support" preferences (AFFREC) for each independent variable (RACE and SEX). White Black Other Chi-Square Asymp. Sig Percentage Support Male Female Chi-Square Asymp. Sig. Percentage Support 3. (RACE) Do the percentages change or move between categories of the variable, signifying a relationship between RACE and AFFREC? Explain how you know. 4. (RACE) What is the significance of chi-square? Is it less than, equal to, or more than .05? 5. (RACE) Is the relationship between RACE and AFFREC statistically significant? 6. (SEX) Do the percentages change or move between categories of the variable, signifying a relationship between SEX and AFFREC? Explain how you know. 7. (SEX) What is the significance of chi-square? Is it less than, equal to, or more than .05? 8. (SEX) Is the relationship between SEX and AFFREC statistically significant? 9. Choose two variables from the data set (nominal and/or ordinal) that you think may be related. List the variables, and explain briefly how you think they are related 10. Explore the relationship between the variables using crosstabs and chi-square. Print your output and describe your findings in a few sentences, focusing in particular on whether the relationship between the variables you chose is statistically significant