set: GSS. Variables: intsex, fepol, fefam, wtss.) Untruthful answers by survey ents can create big headaches for public opinion researchers. Why might a respondent an interviewer the truth? Certain types of questions, combined with particular ristics of the interviewer, can trigger a phenomenon called preference falsification: "the isrepresenting one's genuine wants under perceived social pressures." - For example, the difficulty in gauging opinions on the role of women in society. One might bly expect people questioned by a female interviewer to express greater support for views than those questioned by a male pollster. Someone who supports traditional oles, not wanting to appear insensitive to a female questioner, might instead offer a false inist opinion. 5 dataset contains intsex, which is coded 1 and labeled "Male" for respondents ed by a male interviewer and coded 2 and labeled "Female" for those questioned by a interviewer. This is the independent variable that will allow you to test two preference tion hypotheses: sis 1: In a comparison of individuals, those questioned by a female interviewer will be cely to disagree with the proposition that women are unsuited for politics than will those ed by a male interviewer. (The dependent variable is fepol, coded 1 for "Agree" and 2 agree.") sis 2: In a comparison of individuals, those questioned by a female interviewer will be cely to disagree with the statement that it's better for men to work and women to tend an will those questioned by a male interviewer. (The dependent variable is fefam, which 1 for "Strongly Agree," 2 for "Agree," 3 for "Disagree," and 4 for "Strongly Disagree".) a cross-tabulation analysis analyzing the relationship between intsex and fepol. Make request column percentages and use weights. Complete the cross-tabulations that follow. Interviewer's Statement: Women are not suited for Gender Total politics. Male Female Percentage who "Agree" Percentage who "Disagree" 2