Consider the R output and model below.

Keeping all other variables constant, is it more or less likely that a potential donor makes a donation if the number of dependents in the donor's household increases? Please justify your answer with specific numerical evidence from the R output.

Keeping all other variables constant, is it more or less likely that a younger donor $($e$.$g$.,20$ year$-$old$)$ makes a donation or an older potential donor $($e$.$g$.,60$ yearold$)?$ Please justify your answer with specific numerical evidence from the R output.

Variables of interest:

donationbinary : whether or not a donor contributes this year; $0$ if no contribution, $1$ otherwise

age : age of donor

householdincome : household income of donor

pctemployment : employment percentage of donor; $0$ is unemployed, $1$ is fully employed, other indicates part time percentage worked weekly $($e$.$g$..25$ or $.5)$

householddependents : number of dependents in donor household

For ALL problems, level of significance $a=0\mathrm{.}05$

Call:

glm$($formula $=$ dSdonationbinary $$ dSage $+$ d$householdincome $+$

dSpctemployment $+$ dShouseholddependents, family $=$ "binomial"$)$

Deviance Residuals:

Min $1Q$ Median $3Q$ Max

$-5\mathrm{.}2606,0\mathrm{.}0157,0\mathrm{.}0514,0\mathrm{.}1482,2\mathrm{.}8310$

Coefficients:

$\backslash$table$[[,$Estimate,Std$.$ Error,$z$ value,Pr $)>(|z|,],[($Intercept