Answer:
Step-by-step explanation:
We would apply the formula for determining simple interest which is expressed as
I = PRT/100
Where
I = interest at the end of t years
r represents the interest rate.
P represents the principal or initial amount deposited.
t represents the number of years of investment.
From the information given,
P = 1000
R = 2%
T = 5 years
Therefore,
I = (1000 × 2 × 5)/100
I = $100
The total amount in the account after 5 years would be
1000 + 100 = $1100
Answer:
Step-by-step explanation:
Give the DE
dy/dx = 1-y
Using variable separable method
dy = (1-y)dx
dx = dy/(1-y)
Integrate both sides
∫dx = ∫dy/(1-y)
∫dy/(1-y)= ∫dx
-ln(1-y) = x+C
ln(1-y)^-1 = x+C
Apply e to both sides
e^ln(1-y)^-1 = e^,(x+C)
(1-y)^-1 = Ce^x
1/(1-y) = Ce^x
3 over 1 + 6 over 60
[3 over 1 × 60 over 60] + 6 over 60
180 over 60 + 6 over 60 ➡ 186 over 60
186 over 60 ➡ 31 over 10
Then we divide 31 from 10 which give you the quotient of 3.1..
(((Meaning ➡ '"3.1" would be your answer)))
The answer is =, because in addition, it doesn't matter what order you add things in, it comes out the same.
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.
