Question

# Please show all work A researcher is interested in understanding the predictors of why individuals bully...

A researcher is interested in understanding the predictors of why individuals bully other individuals.  She collects the following data.

 ID of Respondent # of Friends who Bully Respondent was a Bully Victim (0 = No; 1 = Yes) Gender (0 = Female; 1 = Male) # of Times Respondent Bullied Others 1 2 1 1 5 2 4 1 0 2 3 3 0 1 8 4 2 0 0 4 5 6 1 1 6 6 3 0 0 2 7 7 1 1 7 8 4 0 0 0 9 2 1 1 1 10 7 1 1 8

If the researcher used all of these variables to predict whether a respondent was a Bully, which variable (# of friends who bully, respondent was a bully victim, or gender) do you believe would be the strongest predictor? Why?

Here I attach the R code and output

fit=lm(data\$respondendbullied~data\$nofriends+data\$respondentbullyvictim+data\$gender)
summary(fit)

Here the response variable used are No. of friends who bully, respondent was a bully victim, or gender

Coefficients:
Estimate Std. Err t value Pr(>|t|)
(Intercept) 0.4909 1.6418 0.299 0.7750
nofriends 0.6395 0.4007 1.596 0.1616
respondentbullyvictim -2.2772 1.8084 -1.259 0.2547
gender 4.3623 1.7247 2.529 0.0447 *

From the output given we can see that the variable gender is the only significant one at 0.05 level of significance. Since the p value is 0.0447< 0.05

The strongest predictor is gender

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