Coefficients 
Standard Error 
t Stat 
Pvalue 

Intercept 
121.655 
6.540348 
18.6007 
4.92E05 
Temp. 
1.512364 
0.060771 
24.88626 
1.55E05 
Time Mowing 
12.53168 
1.93302 
6.482954 
0.002918 
Model Equation:
Water =  122 + 1.51*Temperature + 12.5*Mowing Time
Intercept = b(0) = 121.655
Temperature = b(1) = 1.512364
Mowing Time = b(2) = 12.53168
Standard Error = s{b(k)}
s{b(0)} = 6.540348
s{b(1)} = .060771
s{b(2)} = 1.93302
For Testing B(k):
test statistic
*using your own ttable with
in each tail and df = (np) = (74).
For B(0):
t(0) = 121.655
= 18.6007 (t Stat)
6.540348
Pvalue = 4.92E05 = .0000492
Remember MS Excel uses scientific notation.
Click here for a pvalue review.
Conclusion for B(0):
Reject H(0): There is significant evidence to conclude that b(0) should not be dropped from the model.
For B(1):
t(1) = 1.512364
= 24.88626 (t Stat)
.060771
Pvalue = 1.55E05 = .0000155
Remember MS Excel uses scientific notation.
Click here for a pvalue review.
Conclusion for B(1):
Reject H(0): There is significant evidence to conclude that b(1) should not be dropped from the model.
For B(2):
t(2) = 12.53168
= 6.482954 (t Stat)
1.93302
Pvalue = .002918
Click here for a pvalue review.
Conclusion for B(2):
Reject H(0): There is significant evidence to conclude that b(2) should not be dropped from the model.
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