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 "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 $($The problem facing a manager is to assess the impact of factors on full$-$time $($FT$)$ job growth. Specilcally, the manager is intecest in the impact of total werldwide revenues

and full$-$time veluntary turnover on the number of full time jobs added in a year. Data were collected from a sample of $20$ "best companies to work foc. The data includes the total

number of fullime jobs added in the past year, total worldwide revenue $($in $$m$ lillons$),$ and the fult$-$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 $($$milions$)$ and let $x_2$ represent the FT Voluntary Turnover $(\%).$

hat$(Y{)}_1=+|,|x_{1i}+|,|x_2|$

$($Round the constant and $x_2-$coeficlent to the nearest integer as needed. Round the $x_{11}-$ceefficient to four decimal places as needed$)$