Answer:
Answer:8: -4/7x+1 9: y=-x+1
Step-by-step explanation:
I dont knwo the rest just put into slope intercept form
Answer:
A
Step-by-step explanation:
Given (x + h) is a factor of f(x) then f(- h) = 0
Given
p(x) = x³ - 4x² + ax + 20 , with (x + 1) as a factor then
p(- 1) = (- 1)³ - 4(- 1)² - a + 20 = 0 , that is
- 1 - 4 - a + 20 = 0
15 - a = 0 ( subtract 15 from both sides )
- a = - 15 ( multiply both sides by - 1 )
a = 15 , thus
p(x) = x³ - 4x² + 15x + 20
If p(x) is divided by (x + h) then p(- h) is the remainder, so
p(- 2) = (- 2)³ - 4(- 2)² + 15(- 2) + 20 , that is
- 8 - 16 - 30 + 20 = - 34 → A
So the probability of rolling a number greater than 2 is 4/6. So 4/6 times 150 should give you the answer 100.
Answer:
The point which is the midpoint is equally spaced from both ends of the line. We know the coordinates of A and we know the coordinates of M, the midpoint.
Step-by-step explanation:
Answer:


![V(X) = E(X^2)-[E(X)]^2=349.2-(18.6)^2=3.24](https://tex.z-dn.net/?f=V%28X%29%20%3D%20E%28X%5E2%29-%5BE%28X%29%5D%5E2%3D349.2-%2818.6%29%5E2%3D3.24)
The expected price paid by the next customer to buy a freezer is $466
Step-by-step explanation:
From the information given we know the probability mass function (pmf) of random variable X.

<em>Point a:</em>
- The Expected value or the mean value of X with set of possible values D, denoted by <em>E(X)</em> or <em>μ </em>is

Therefore

- If the random variable X has a set of possible values D and a probability mass function, then the expected value of any function h(X), denoted by <em>E[h(X)]</em> is computed by
![E[h(X)] = $\sum_{D} h(x)\cdot p(x)](https://tex.z-dn.net/?f=E%5Bh%28X%29%5D%20%3D%20%24%5Csum_%7BD%7D%20h%28x%29%5Ccdot%20p%28x%29)
So
and
![E[h(X)] = $\sum_{D} h(x)\cdot p(x)\\E[X^2]=$\sum_{D}x^2\cdot p(x)\\ E(X^2)=16^2\cdot 0.3+18^2\cdot 0.1+20^2\cdot 0.6\\E(X^2)=349.2](https://tex.z-dn.net/?f=E%5Bh%28X%29%5D%20%3D%20%24%5Csum_%7BD%7D%20h%28x%29%5Ccdot%20p%28x%29%5C%5CE%5BX%5E2%5D%3D%24%5Csum_%7BD%7Dx%5E2%5Ccdot%20p%28x%29%5C%5C%20E%28X%5E2%29%3D16%5E2%5Ccdot%200.3%2B18%5E2%5Ccdot%200.1%2B20%5E2%5Ccdot%200.6%5C%5CE%28X%5E2%29%3D349.2)
- The variance of X, denoted by V(X), is
![V(X) = $\sum_{D}E[(X-\mu)^2]=E(X^2)-[E(X)]^2](https://tex.z-dn.net/?f=V%28X%29%20%3D%20%24%5Csum_%7BD%7DE%5B%28X-%5Cmu%29%5E2%5D%3DE%28X%5E2%29-%5BE%28X%29%5D%5E2)
Therefore
![V(X) = E(X^2)-[E(X)]^2\\V(X)=349.2-(18.6)^2\\V(X)=3.24](https://tex.z-dn.net/?f=V%28X%29%20%3D%20E%28X%5E2%29-%5BE%28X%29%5D%5E2%5C%5CV%28X%29%3D349.2-%2818.6%29%5E2%5C%5CV%28X%29%3D3.24)
<em>Point b:</em>
We know that the price of a freezer having capacity X is 60X − 650, to find the expected price paid by the next customer to buy a freezer you need to:
From the rules of expected value this proposition is true:
We have a = 60, b = -650, and <em>E(X)</em> = 18.6. Therefore
The expected price paid by the next customer is
