Question

Can we predict the running time for Mr. Degges when he runs 3.1 miles on the track at the NDSU Wellness center?

Need: SAS output to analyze the model

Need: prediction equation

y-hat

SSE SST, error, F-test

What variables are significant

The variables are: Y = running time in minutes X1 = weight at the time of running X2 = number of days between running events

Year X1 X2   Y

2009 191.2 1 29.0

2009 192 1   27.80

2009 190.4 2 28.53

2009 190.4 3 28.10

2009 190.6 2   28

2009 190.6 0   27.43

2009 190.2 0 28

2009 191.8 1    27.27

2009 189.2 12 30.52

2009 189.2 0 28.95

2009 190.2 2 29.08

2015 168.6 14 29.92

2015 166.2 4   29.83

2015 165.0 2 28.37

2015 169.8 6 27.25

2015 169.4 4 27.85

2015 167.2 3 27.58

2015 166.6 2 27.10

Answer 1

	R²	0.420
	Adjusted R²	0.343
	R	0.648
	Std. Error	0.809
	n	18
	k	2
	Dep. Var.	Y
ANOVA table
Source	SS	df	MS	F	p-value
Regression	7.1197	2	3.5598	5.43	.0168
Residual	9.8266	15	0.6551
Total	16.9462	17
Regression output
variables	coefficients	std. error	t (df=15)	p-value
Intercept	23.4215
X1	0.0240	0.0181	1.329	.2038
X2	0.1780	0.0541	3.291	.0049

The model is significant.

X2 is significant.

The prediction equation is:

Y = 23.4215 + 0.0240*X1 + 0.1780*X2