A company would like to estimate its total cost equation using customer records.  The company has randomly...

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A company would like to estimate its total cost equation usingcustomer records.  The company has randomly sampled 28customer records. Each customer record contains a Customer #, theOrder Size, and the Total Cost of the Order.  The analystremembers from accounting and economics classes taken in collegethat

TOTAL COST = Fixed Costs + Variable Cost per Unit *OrderSize.

The analysis sees that this is a linear relationship where theTOTAL COST depends on the Fixed Costs, which do not depend on ordersize, and a variable cost per unit, which is multiplied by theOrder Size.  The analysis decides to use simple linearregression to estimate the firm’s Total Costfunction.  Use the data file, Estimating aTotal Cost Regression Model.xlsx to answer thefollowing questions

  1. Develop a 95% confidence interval for the true average unitvariable cost. (Look at the regression output produced by Excel forpart b.)
  2. What percent of the variation in monthly total costs is“explained” by the regression model with monthly production outputas the explanatory variable? (Look at the regression outputproduced by Excel for part )
  3. Suppose the plant manager is interested in estimating themean total costs for several months whereoutput is 30,000 units (i.e., Xp = 30) each month. Develop a 95%confidence interval for the mean total costs for months thataverage 30,000 units of output.
Customer #Order Size (Quantity)Total Cost of Order
10211281631
10212311923
10213432070
10214472392
10215321886
10216432307
10217251486
10218462448
10219412210
10220482401
10221291860
10222321786
10223492485
10224442203
10225331855
10226462380
10227422102
10228311683
10229301706
10230351955
10231341992
10232331926
10233271852
10234321807
10235311880
10236422134
10237391979
10238361882

Answer & Explanation Solved by verified expert
3.7 Ratings (401 Votes)
using excel we have Simple Linear Regression Analysis Regression Statistics Multiple R 09429 R Square 08891 Adjusted R Square 08848 Standard Error 898751 Observations 28 ANOVA df SS MS F Significance F Regression 1 16839626247 16839626247 2084747 00000 Residual 26 2100160539    See Answer
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