The following computer printout estimated overhead costs using linear regression:

t for H$(0)$ Std$.$ error

Parameter Estimate Parameter $=0$ Pr $>$ t of parameter

Intercept $752\mathrm{.}250\mathrm{.}025033\mathrm{.}33$

Setup hours $135\mathrm{.}100\mathrm{.}00012\mathrm{.}45$

# of parts $501\mathrm{.}650\mathrm{.}050030\mathrm{.}30$

R Square $($R$2)0\mathrm{.}83$

Standard Error $($Se$)50\mathrm{.}00$

Observations $70$

Required:

a$.$ Write the multiple regression model.

b$.$ What does R Square mean?

c$.$ Provide a $95$ percent confidence interval around the number of parts parameter.

a$.$ Overhead costs $=$ $$75+$ $$13($setup hours$)+$ $$50($# of parts$)$

b$.$ Eighty$-$three percent of the variation in overhead costs is explained by setup hours and number of

parts.

c$.$ df $=70-3=67$

t is $1\mathrm{.}65$

$$50\backslash$pm $1\mathrm{.}65(30\mathrm{.}30)=[$$$(\mathrm{.}005),$ $$99\mathrm{.}995]$