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.
I'd suggest you write "6 2/5," not "6 and 2/5."
6 2/5 rotations
-------------------- =
2 2/3 seconds
32
---
5 32 3
------- = ------ * -----
8 5 8 Reduce that 32/8: obtain 4.
---
3
Then we have
4(3)/5, or 12/5 rotations per sec.
The larger fractron will be the fraction with the greater numerator.
ex. 4/5 is greater than 2/5
1.50x + 450 = 3x
450 = 3x - 1.50x
450 = 1.50x
450/1.50 = x
300 = x
300 copies must be sold to break even
Answer:
x=7
Step-by-step explanation:
