Result:
Excel Addon Megastat used.
Regression Analysis |
|||||||
R² |
0.844 |
||||||
Adjusted R² |
0.826 |
n |
30 |
||||
R |
0.919 |
k |
3 |
||||
Std. Error of Estimate |
66.071 |
Dep. Var. |
y |
||||
Regression output |
confidence interval |
||||||
variables |
coefficients |
std. error |
t (df=26) |
p-value |
95% lower |
95% upper |
|
Intercept |
a = |
103.120 |
71.989 |
1.432 |
.1639 |
-44.855 |
251.094 |
vol.traffic |
b1 = |
1.365 |
0.122 |
11.155 |
0.0000 |
1.114 |
1.617 |
max temp |
b2 = |
0.274 |
0.126 |
2.181 |
.0384 |
0.016 |
0.533 |
average drink |
b3 = |
23.908 |
18.510 |
1.292 |
.2079 |
-14.140 |
61.956 |
ANOVA table |
|||||||
Source |
SS |
df |
MS |
F |
p-value |
||
Regression |
612,671.894 |
3 |
204,223.965 |
46.78 |
0.0000 |
||
Residual |
113,501.473 |
26 |
4,365.441 |
||||
Total |
726,173.367 |
29 |
a).
y = 103.120+1.365*vol. traffic +0.274*max temp+23.908*average drink price
b).
null hypothesis for F test is rejected.
c).
R square = 0.844
d).
value for s =66.071
e).
least significant explanatory variable =
average drink price
f).
Regression Analysis |
|||||||
R² |
0.834 |
||||||
Adjusted R² |
0.821 |
n |
30 |
||||
R |
0.913 |
k |
2 |
||||
Std. Error of Estimate |
66.884 |
Dep. Var. |
y |
||||
Regression output |
confidence interval |
||||||
variables |
coefficients |
std. error |
t (df=27) |
p-value |
95% lower |
95% upper |
|
Intercept |
a = |
167.906 |
52.272 |
3.212 |
.0034 |
60.652 |
275.159 |
vol.traffic |
b1 = |
1.374 |
0.124 |
11.103 |
0.0000 |
1.120 |
1.628 |
max temp |
b2 = |
0.269 |
0.127 |
2.111 |
.0442 |
0.008 |
0.530 |
ANOVA table |
|||||||
Source |
SS |
df |
MS |
F |
p-value |
||
Regression |
605,389.318 |
2 |
302,694.659 |
67.66 |
0.0000 |
||
Residual |
120,784.049 |
27 |
4,473.483 |
||||
Total |
726,173.367 |
29 |
|||||
y = 167.906+1.374*vol. traffic +0.269*max temp
g).
new value of R square =0.834
decreased
h).
new value of s=66.884
increased
i).
the better model is
original model.
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