Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:

Month Machine Hours Electricity Costs

January $2,200$ $ $19,050$

February $2,600$ $ $22,300$

March $1,600$ $ $14,150$

April $2,800$ $ $24,300$

May $3,500$ $ $28,900$

June $3,000$ $ $23,300$

July $3,800$ $ $25,400$

August $3,200$ $ $23,400$

September $1,700$ $ $16,800$

October $3,400$ $ $27,300$

November $4,400$ $ $32,300$

December $3,900$ $ $28,400$

Summary Output

Regression Statistics

Multiple R $0\mathrm{.}958$

R Square $0\mathrm{.}918$

Adjusted R$20\mathrm{.}910$

Standard Error $1,572\mathrm{.}21$

Observations $12\mathrm{.}00$

Coefficients Standard Error t Stat P$-$value Lower $95\%$ Upper $95\%$

Intercept $6,468\mathrm{.}831,698\mathrm{.}623\mathrm{.}810\mathrm{.}002,684\mathrm{.}0610,253\mathrm{.}60$

Machine Hours $5\mathrm{.}760\mathrm{.}5410\mathrm{.}590\mathrm{.}004\mathrm{.}556\mathrm{.}97$

If the controller uses regression analysis to estimate costs, the estimate of the fixed portion of electricity costs is:

Multiple Choice

Fixed Cost $=$ $$5\mathrm{.}76.$

Fixed Cost $=$ $$6,468\mathrm{.}83.$

Fixed Cost $=$ $$1,698\mathrm{.}62.$

Fixed Cost $=$ $$1,572\mathrm{.}21.$