Step-by-step explanation:
First, note that a flexible statistical learning method refers to using models that take into account agree difference in the observed data set, and are thus adjustable. While the inflexible method usually involves a model that has no regard to the kind of data set.
a) The sample size n is extremely large, and the number of predictors p is small. (BETTER)
In this case since the sample size is extremely large a flexible model is a best fit.
b) The number of predictors p is extremely large, and the number of observations n is small. (WORSE)
In such case overfiting the data is more likely because of of the small observations.
c) The relationship between the predictors and response is highly non-linear. (BETTER)
The flexible method would be a better fit.
d) The variance of the error terms, i.e. σ2=Var(ϵ), is extremely high. (WORSE)
In such case, using a flexible model is a best fit for the error terms because it can be adjusted.
Step-by-step explanation:
log2x = 1 - log(x+4)
log2x = log10 - log(x+4)
log2x = log[10/(x+4)]
2x = 10/(x+4)
2x(x+4) = 10
2x² + 8x - 10 = 0
÷2 both sides of equation
x² + 4x - 5 = 0
(x+5)(x-1) = 0
x = -5, 1
x isn't be -5 because logA, A need to be > 0
So, x value is 1
63 5 tens=50
13 ones=10 and 3 leftover 50+13=63
Answer:
3/5
Step-by-step explanation:
To have the best chance of pulling a pair with the same color you should try to get a pair of black socks. There is a 3/5 chance of pulling a black sock so this means for every 5 socks you pull you get 3 black socks or 2 navy socks. Either way you will get a pair of socks with the same color. (Double check to make sure I'm correct)
Answer:
-175
Step-by-step explanation:
5x4=20
30x2=60
20-60=-40
-40-135=175
I hope this helps!
