After looking at MLs, the researcher decides to look at the entire sample. In her analysis the researcher is interested in the relationship between party affiliation, gender, and religious importance. She measures party affiliation on a seven-point scale such that: 1-Strong Democrat; 2=Democrat; 3=Independent leaning Democrat; 4=Independent; 5=Independent leaning Republican; 6=Republican; 7=Strong Republican. Gender is measured as a dummy variable coded 1 if the respondent identifies as female and O if the respondent identifies as male. Religious importance is coded as before (1=important; O=unimportant). A regression model is estimated and the following results are obtained: Call: Im(formula = guncontrol ~ pid7 + ex + ri, data = therms) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 15.82 0.13 117.89 <0.0000000000000002 pid7 -1.02 0.03 sex 1.43 0.11 ri High -0.30 0.12 Note that "pid7" denotes the party affiliation measure; "sex" measures gender identification (1=female; O=male); and "riHigh" measures religious importance (1-high; 0=low). Write out the regression equation the researcher estimates using the estimates from above.

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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After looking at MLs, the researcher decides to look at the entire sample. In her analysis the
researcher is interested in the relationship between party affiliation, gender, and religious
importance. She measures party affiliation on a seven-point scale such that: 1-Strong Democrat;
2-Democrat; 3=Independent leaning Democrat; 4=Independent; 5=Independent leaning Republican;
6=Republican; 7=Strong Republican. Gender is measured as a dummy variable coded 1 if the
respondent identifies as female and O if the respondent identifies as male. Religious importance is
coded as before (1-important; O=unimportant).
A regression model is estimated and the following results are obtained:
Call:
Im(formula = guncontrol ~ pid7 + sex + ri, data = therms)
Coefficients:
Estimate Std. Error t value
Pr(>|t|)
(Intercept) 15.82 0.13 117.89 <0.0000000000000002
pid7
-1.02 0.03
sex
1.43 0.11
ri High -0.30 0.12
Note that "pid7" denotes the party affiliation measure; "sex" measures gender identification
(1=female; O=male); and "riHigh" measures religious importance (1=high; 0=low).
Write out the regression equation the researcher estimates using the estimates from above.
Transcribed Image Text:After looking at MLs, the researcher decides to look at the entire sample. In her analysis the researcher is interested in the relationship between party affiliation, gender, and religious importance. She measures party affiliation on a seven-point scale such that: 1-Strong Democrat; 2-Democrat; 3=Independent leaning Democrat; 4=Independent; 5=Independent leaning Republican; 6=Republican; 7=Strong Republican. Gender is measured as a dummy variable coded 1 if the respondent identifies as female and O if the respondent identifies as male. Religious importance is coded as before (1-important; O=unimportant). A regression model is estimated and the following results are obtained: Call: Im(formula = guncontrol ~ pid7 + sex + ri, data = therms) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 15.82 0.13 117.89 <0.0000000000000002 pid7 -1.02 0.03 sex 1.43 0.11 ri High -0.30 0.12 Note that "pid7" denotes the party affiliation measure; "sex" measures gender identification (1=female; O=male); and "riHigh" measures religious importance (1=high; 0=low). Write out the regression equation the researcher estimates using the estimates from above.
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