BECAUSE THERE IS A Y AXIS AND AN X AXIS THOSE R THE 2 GIVIN LINES
Answer:
sln
b3=8(dived by 3 both sides)
b=8/3
I hope this help you
10(0.5x + 6) = 8
5x + 60 = 8
5x = 8 - 60
5x = -52
x = -52/5
x = -10.4
Answer:
See the proof below.
Step-by-step explanation:
For this case we just need to apply properties of expected value. We know that the estimator is given by:
![S^2_p= \frac{(n_1 -1) S^2_1 +(n_2 -1) S^2_2}{n_1 +n_2 -2}](https://tex.z-dn.net/?f=S%5E2_p%3D%20%5Cfrac%7B%28n_1%20-1%29%20S%5E2_1%20%2B%28n_2%20-1%29%20S%5E2_2%7D%7Bn_1%20%2Bn_2%20-2%7D)
And we want to proof that ![E(S^2_p)= \sigma^2](https://tex.z-dn.net/?f=E%28S%5E2_p%29%3D%20%5Csigma%5E2)
So we can begin with this:
![E(S^2_p)= E(\frac{(n_1 -1) S^2_1 +(n_2 -1) S^2_2}{n_1 +n_2 -2})](https://tex.z-dn.net/?f=E%28S%5E2_p%29%3D%20E%28%5Cfrac%7B%28n_1%20-1%29%20S%5E2_1%20%2B%28n_2%20-1%29%20S%5E2_2%7D%7Bn_1%20%2Bn_2%20-2%7D%29)
And we can distribute the expected value into the temrs like this:
![E(S^2_p)= \frac{(n_1 -1) E(S^2_1) +(n_2 -1) E(S^2_2)}{n_1 +n_2 -2}](https://tex.z-dn.net/?f=E%28S%5E2_p%29%3D%20%5Cfrac%7B%28n_1%20-1%29%20E%28S%5E2_1%29%20%2B%28n_2%20-1%29%20E%28S%5E2_2%29%7D%7Bn_1%20%2Bn_2%20-2%7D)
And we know that the expected value for the estimator of the variance s is
, or in other way
so if we apply this property here we have:
![E(S^2_p)= \frac{(n_1 -1 )\sigma^2_1 +(n_2 -1) \sigma^2_2}{n_1 +n_2 -2}](https://tex.z-dn.net/?f=E%28S%5E2_p%29%3D%20%5Cfrac%7B%28n_1%20-1%20%29%5Csigma%5E2_1%20%2B%28n_2%20-1%29%20%5Csigma%5E2_2%7D%7Bn_1%20%2Bn_2%20-2%7D)
And we know that
so using this we can take common factor like this:
![E(S^2_p)= \frac{(n_1 -1) +(n_2 -1)}{n_1 +n_2 -2} \sigma^2 =\sigma^2](https://tex.z-dn.net/?f=E%28S%5E2_p%29%3D%20%5Cfrac%7B%28n_1%20-1%29%20%2B%28n_2%20-1%29%7D%7Bn_1%20%2Bn_2%20-2%7D%20%5Csigma%5E2%20%3D%5Csigma%5E2)
And then we see that the pooled variance is an unbiased estimator for the population variance when we have two population with the same variance.
Answer:
5+(-3)-6
= 5+(-9)
= -4
Step-by-step explanation:
Hope it helps..