Answer:
they are complementary
Step-by-step explanation:
Vcone=1/3(hpir^2)
Vsphere=(4/3)pir^3
evaluate
vcone=1/3(1pi1^2)=pi/3
vsphere=4/3pi1^3=4pi/3
pi/3 times what=4pi/3
times both sides by 3
pi times what=4pi
divide both sides by pi
1 times what=4
what=4
4 cones
Answer:
Step-by-step explanation:
Ac²= AB²+ BC²
Ac²= 4²+15²= 16+225
Square both side
Ac = √241= 15.52cm
Step-by-step explanation:
To check out how efficient or accurate a model is, we use the akaike information criterion or the Bayesian. If the AIC or BIC are lower, then this model would be better. They are also used to control for model complexity
Akaike information criterion = 2k-2ln where k is the number of parameter. A higher k gives a higher AIC.
In the real world complex models are discouraged and avoided since
1. They cause data to be over fitted and can capture noise and information from this data.
2. They are complex and therefore difficult to interpret
3. They consume a lot of time and computing them has several inefficiencies.
Using these two as measure of performance, we can select optimal choice of independent variable.
With forward/backward regression, we are able to put new variables in the model or remove from it. The best is the one with lowest AIC.
