Question

Consider the dataset below for lead residue as an effect of number of pistons in an engine:

Number of Pistons Lead (Parts per Million)

2 (45)

4 (38)

6 (24)

8 (32)

10 (12)

12 (4)

Using SPSS, create a scatterplot of the data, graph the least-squares regression line, and find the correlation. Are there any influential points (and how do you recognize them)? How many parts per million of lead should we expect when there are five pistons? Be sure to export your outputs to a Word document in order to edit the graphs and statistics together and remove unnecessary computer code and notes.

Answer 1

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.9392
R Square	0.8820
Adjusted R Square	0.8526
Standard Error	6.0099
Observations	6
ANOVA
	df	SS	MS	F	Significance F
Regression	1	1080.3571	1080.3571	29.9110	0.0054
Residual	4	144.4762	36.1190
Total	5	1224.8333
	Coefficients	Standard Error	t Stat	P-value	Lower 95%
Intercept	53.3333	5.5949	9.5325	0.0007	37.7993
x	-3.9286	0.7183	-5.4691	0.0054	-5.9230

y^ = 53.3333 -3.9286 *x

r = -0.9392

when x= 5

y^ = 53.3333 -3.9286 *5 = 33.6903