Question

all 3 requirments

Question 8, E6-27A (book/static) IE Question Help a flat delivery fee Logh wants van operating costs so that she Melody Leigh, owner of Broadway Floral operates a local chain of floral Shops. Each shop has its own delivery van. Instead of ch to set the delivery fee based on the distance driven to deliver the flowers Leigh wants to separate the fixed and variable portions has a better idea how delivery distance affects these costs. She has the following data from the past seven months (Click the icon to view the data) Read the requirements Requirement 1. Determine the company's cost equation (use the output from the Excel regression). (Round the amounts to two decimal places.) yos a xos Requirements Data Table Month Van Operating costs Use Microsoft Excel to run a regression analysis, then do the following Determine the company's cost equation (use the output from the Excel regression) Determine the R-square (use the output from the Excel regression) What does Broadway Florals Roure indicate? Predict van operating costs at a volume of 16 500 miles assuming the company would use the cost equation from the Excel regression regardless of its R-square. Should the company rely on this cost estimate? Why or why not? January Miles Driven 15,500 17.400 15.400 16,300 16,500 15 200 14.400 February March April $5280 $4,960 $5 340 $5,450 $5230 54680 Print Done Print Done Clear All Check Answer

Answer 1

Here y variable is the van operating costs and x variable is the miles driven. The above data is inputted in excel and then “regression” function is used which yields the following result:

	Coefficients
Intercept	2163.80
X Variable 1	0.19

(1): Thus the cost equation will be: y = $0.19x + $2,163.80

(2): The r-square is 0.4746 (4 decimal places) or 0.47 (2 decimal places). Broadway Floral's r square indicates that around 47.46% of variation in the dependent variable (i.e. costs) is explained by the independent variable (i.e. miles driven) in this case.

(3): Here x = 16,500 miles. Thus cost = 0.19*16,500 + 2163.80

= $5,298.80

No the company should not rely on this cost estimate too much because of the fact that R square value is low and hence the data are not too closely fitting the regression line. As the fit for the model is not very good we can say that the company should not rely too much on this cost estimate.

The summary output of regression function in excel is attached below for your reference:

q quant 2019 20 - Microsoft Excel Page Layout Formulas Data Review View N15 File Home Insert % Cut Ea Copy Paste Format Painter B Clipboard Calibri 11 A A == Wrap Text General 1 - Autosum A7 Fill - I U 1 A Fa Merge & Center % 4 ,99 Conditional Format Formatting as Table Styles Cell Styles Insert Delete Format 2 Clear Sort & Find & Filter Select Editing Alignment E Number Cells Font foc SUMMARY OUTPUT AL C D E F G H I J K L M N O P Q R B 1 SUMMARY OUTPUT 2 3 Regression Statistics 4 Multiple R 0.688906607 5 R Square 0.4746 6 Adjusted R Square 0.369510775 7 Standard Error 218.1305117 8 Observations 7 9 df 10 ANOVA 11 12 Regression 13 Residual 14 Total F gnificance F 4.51642 0.086932 SS MS 1 214895.4 214895.4 5 237904.6 47580.92 6 452800 15 16 17 Intercept 18 X Variable 1 19 Coefficients andard Errt Stat P-value Lower 95%Upper 95%ower 95.09pper 95.0% 2163.80 1426.351 1.517021 0.189709 -1502.75 5830.358 -1502.75 5830.358 0.19 0.090043 2.125187 0.086932 -0.0401 0.422821 -0.0401 0.422821 3135 23 24 ► Ready April May June July Aug Sept Oct Nov Dec Jan Feb Sheet2 Sheet1 [ 000 100% 0 EN Pť 1 10:24 17/02/2020

(3):