The problem facing a manager is to assess the impact of factors on full$-$time $($FT$)$ job growth. Specifically, the manager is interest in the impact of total worldwide revenues and full$-$time voluntary turnover on the number of full$-$time jobs added in a year. Data were collected from a sample of $20$ "best companies to work for." The data includes the total number of full$-$time jobs added in the past year, total worldwide revenue $($in $millions$),$ and the full$-$time voluntary turnover $(\%).$ Use the accompanying data to complete parts $($a$)$ through $($d$)$ below.

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a$.$ State the multiple regression equation.

Let $x_1$ represent the Total Worldwide Revenues $($$millions$)$ and let $x_2$ represent the FT Voluntary Turnover $(\%).$

hat$(Y{)}_i=+||x_{1i}+|,x_{2i}||$

$($Round the constant and $x_{2i}$ todbeficieatest integer as needed. Round the $x_{1i}$ todefficiedtimal places as needed.$)$

Data of Best Companies to Work For

$\backslash$table$[[\backslash$table$[[$Total FT$],[$Jobs Added Revenues $($$millions$)]],\backslash$table$[[$Turnover $(\%)],[$Total Wold$]],],[178,3,900\mathrm{.}000,5\mathrm{.}990],[228,25,364\mathrm{.}000,5\mathrm{.}617],[569,1,309\mathrm{.}239,6\mathrm{.}996],[193,1,144\mathrm{.}000,5\mathrm{.}351],[-67,3,691\mathrm{.}728,12\mathrm{.}764],[263,332\mathrm{.}268,1\mathrm{.}950],[1,085,15,000\mathrm{.}000,3\mathrm{.}287],[1,654,10,960\mathrm{.}000,15\mathrm{.}644],[94,2,029\mathrm{.}893,2\mathrm{.}000],[-13,2,544\mathrm{.}000,4\mathrm{.}781],[329,236\mathrm{.}698,7\mathrm{.}893],[86,696\mathrm{.}200,5\mathrm{.}233],[415,8,843\mathrm{.}900,4\mathrm{.}504],[1,886,20,729\mathrm{.}000,7\mathrm{.}451],[238,3,700\mathrm{.}000,14\mathrm{.}821],[4,040,21,396\mathrm{.}000,13\mathrm{.}136],[-224,11,220\mathrm{.}000,5\mathrm{.}032],[87,290\mathrm{.}401,4\mathrm{.}559],[314,3,319\mathrm{.}000,18\mathrm{.}283],[1,264,12,316\mathrm{.}379,20\mathrm{.}038]]$