R^: How much of the data does this model explain from 0-1
Our case r^2= .8216 meaning the model can explain 82.16% of the data
We reject the Null
Significance F is less then Alpha, so we have a good model
Coefficient: Positive or negative? What is the relationship between Dependent X and Independent Y
P-Value: is it a good variable? P smaller then Alpha
Does it make sense?
Intercept
Africa
Status
Adult
Mortality
BMI
Polio
Diphtheria
Standard
Coefficients
Error
68.786 1.58714209
-5.516 0.73227415
3.884 0.76207075
-0.035 0.00341567
0.047 0.0148943
0.047 0.01472055
t Stat
P-value
Lower 95%
43.339332 1.8513E-93 65.6525001
7.53310804 2.8522E-12 6.96188305
5.09691366 9.1703E-07 2.37980459
10.2878289 1.3959E-19 0.04188273
3.15744611 0.00188528 0.0176251
3.18318215 0.00173416 0.01779835
0.038 0.01615783 2.37940103
Lower
Upper 95%
99.0%
71.918856 64.650802
4.07071758 7.4240452
5.38861299 1.8988368
0.02839697 0.0440384
0.07643077 0.0082248
0.07591804 0.0085077
0.0184556 0.00654878 0.07034315 0.0036489