By applying the formulas of present and future values of annuity we can solve this problem. In this mortgage problem, first we have to find loan amount after the down payment. It is 699,000 - 699,000 * 0.2 = 559,200$. We have to set it as PV (Present Value) of annuity. Using the PV formula ![PV = A \frac{[1- \frac{1}{(1+r)^{N}}]}{r}](https://tex.z-dn.net/?f=%20PV%20%3D%20A%20%5Cfrac%7B%5B1-%20%5Cfrac%7B1%7D%7B%281%2Br%29%5E%7BN%7D%7D%5D%7D%7Br%7D%20)
, we first find A, which is an annual payment. Exact calculation with mortgage calculator gives us A = 33,866.56$. After finding it, plugging this number into FV (Future Value) formula ![FV = A\frac{[(1+r)^{N}-1]}{r}](https://tex.z-dn.net/?f=%20FV%20%3D%20A%5Cfrac%7B%5B%281%2Br%29%5E%7BN%7D-1%5D%7D%7Br%7D%20%20%20)
, we find the value of the future value and it is 1,185,329.66$. And the total financial charge is 1,185,329.66 - 559,200 = 626,129.66$
Answer:
(x, y) = (3, 5)
Step-by-step explanation:
Solving by elimination here again, there are 2 good options available. Either multiply the whole bottom equation by -1 to cancel the x, or by 2 to cancel the y. I'll do the latter:
Add from top to bottom:
Now, with the value of x, solve for y in either of the equations. I'll choose the second one here:
(x, y) = (3, 5)
The sum of the function will be (r – s)(x) = –2x² + x – 3, The difference of the function will be (r – s)(x) = –2x² + x – 3, and The product of the function will be (r × s)(x) = 2x³ – 6x².
The complete question is attached below.
<h3>What is Algebra?</h3>
The analysis of mathematical representations is algebra, and the handling of those symbols is logic.
The functions are given below.
r(x) = x – 3
s(x) = 2x²
The sum of the function will be
(r + s)(x) = x – 3 + 2x²
(r + s)(x) = 2x² + x – 3
The difference of the function will be
(r – s)(x) = (x – 3) – 2x²
(r – s)(x) = –2x² + x – 3
The product of the function will be
(r × s)(x) = (x – 3) (2x²)
(r × s)(x) = 2x³ – 6x²
More about the Algebra link is given below.
brainly.com/question/953809
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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.
