Question

In a manufacturing process the assembly line speed (feet per minute)was thought to affect the number of defective parts found during the inspection process. To test this theory, managers devised a situation in which the same batch of parts was inspected visually at a variety of line speeds. The collected the following data: Line Speed 20 20 40 30 60 40 Number of Defective Parts Found 21 19 15 16 15 8 . Use four digits of accuracy for your answers. Use the data to develop an estimated regression equation that could be used to predict the number of defective parts found, given the line speed. What is the estimated regression model (Enter b0 and b1)? How much of the variation in the number of defective parts is explained by your regression model (R Square)? Please show your work in EXCEL.

1) b0 - Intercept

2) b1

3) R Square

Answer 1

Line speed	No. of defective Parts
20	21
20	19
40	15
30	16
60	15
40	8

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.562156
R Square	0.31602
Adjusted R Square	0.145025
Standard Error	4.121348
Observations	6
ANOVA
	df	SS	MS	F	Significance F
Regression	1	31.3913	31.3913	1.848123	0.245592
Residual	4	67.94203	16.98551
Total	5	99.33333
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	21.44928	4.574295	4.689089	0.009384	8.748996	34.14955	8.748996	34.14955
Line speed	-0.16522	0.121532	-1.35946	0.245592	-0.50264	0.172209	-0.50264	0.172209

= 21.4493

= -0.1652

= 31.60%

Number of defective Parts = 21.4493 - 0.1562 * Line Speed

The variation in the number of defective parts is explained by your regression model is 31.60%