9514 1404 393
Answer:
no
Step-by-step explanation:
Put 2 where x is and see if you get a true statement.
1/2(2) -4 = 5
1 -4 = 5
-3 = 5 . . . . . . False
2 is not a solution to the equation.
__
The solution is x=18.
Let
![X](https://tex.z-dn.net/?f=X)
denote the random variable for the weight of a swan. Then each swan in the sample of 36 selected by the farmer can be assigned a weight denoted by
![X_1,\ldots,X_{36}](https://tex.z-dn.net/?f=X_1%2C%5Cldots%2CX_%7B36%7D)
, each independently and identically distributed with distribution
![X_i\sim\mathcal N(26,7.2)](https://tex.z-dn.net/?f=X_i%5Csim%5Cmathcal%20N%2826%2C7.2%29)
.
You want to find
![\mathbb P(X_1+\cdots+X_{36}>1000)=\mathbb P\left(\displaystyle\sum_{i=1}^{36}X_i>1000\right)](https://tex.z-dn.net/?f=%5Cmathbb%20P%28X_1%2B%5Ccdots%2BX_%7B36%7D%3E1000%29%3D%5Cmathbb%20P%5Cleft%28%5Cdisplaystyle%5Csum_%7Bi%3D1%7D%5E%7B36%7DX_i%3E1000%5Cright%29)
Note that the left side is 36 times the average of the weights of the swans in the sample, i.e. the probability above is equivalent to
![\mathbb P\left(36\displaystyle\sum_{i=1}^{36}\frac{X_i}{36}>1000\right)=\mathbb P\left(\overline X>\dfrac{1000}{36}\right)](https://tex.z-dn.net/?f=%5Cmathbb%20P%5Cleft%2836%5Cdisplaystyle%5Csum_%7Bi%3D1%7D%5E%7B36%7D%5Cfrac%7BX_i%7D%7B36%7D%3E1000%5Cright%29%3D%5Cmathbb%20P%5Cleft%28%5Coverline%20X%3E%5Cdfrac%7B1000%7D%7B36%7D%5Cright%29)
Recall that if
![X\sim\mathcal N(\mu,\sigma)](https://tex.z-dn.net/?f=X%5Csim%5Cmathcal%20N%28%5Cmu%2C%5Csigma%29)
, then the sampling distribution
![\overline X=\displaystyle\sum_{i=1}^n\frac{X_i}n\sim\mathcal N\left(\mu,\dfrac\sigma{\sqrt n}\right)](https://tex.z-dn.net/?f=%5Coverline%20X%3D%5Cdisplaystyle%5Csum_%7Bi%3D1%7D%5En%5Cfrac%7BX_i%7Dn%5Csim%5Cmathcal%20N%5Cleft%28%5Cmu%2C%5Cdfrac%5Csigma%7B%5Csqrt%20n%7D%5Cright%29)
with
![n](https://tex.z-dn.net/?f=n)
being the size of the sample.
Transforming to the standard normal distribution, you have
![Z=\dfrac{\overline X-\mu_{\overline X}}{\sigma_{\overline X}}=\sqrt n\dfrac{\overline X-\mu}{\sigma}](https://tex.z-dn.net/?f=Z%3D%5Cdfrac%7B%5Coverline%20X-%5Cmu_%7B%5Coverline%20X%7D%7D%7B%5Csigma_%7B%5Coverline%20X%7D%7D%3D%5Csqrt%20n%5Cdfrac%7B%5Coverline%20X-%5Cmu%7D%7B%5Csigma%7D)
so that in this case,
![Z=6\dfrac{\overline X-26}{7.2}](https://tex.z-dn.net/?f=Z%3D6%5Cdfrac%7B%5Coverline%20X-26%7D%7B7.2%7D)
and the probability is equivalent to
![\mathbb P\left(\overline X>\dfrac{1000}{36}\right)=\mathbb P\left(6\dfrac{\overline X-26}{7.2}>6\dfrac{\frac{1000}{36}-26}{7.2}\right)](https://tex.z-dn.net/?f=%5Cmathbb%20P%5Cleft%28%5Coverline%20X%3E%5Cdfrac%7B1000%7D%7B36%7D%5Cright%29%3D%5Cmathbb%20P%5Cleft%286%5Cdfrac%7B%5Coverline%20X-26%7D%7B7.2%7D%3E6%5Cdfrac%7B%5Cfrac%7B1000%7D%7B36%7D-26%7D%7B7.2%7D%5Cright%29)
1. Julia's ≤ Rachel's hair
2. 40 < 74
Answer:
A. 49
Step-by-step explanation:
The average rate of change for the interval ranging from x = 3 to x = 5 for the given function represented in the table above can be calculated using:
![Average rate of change = \frac{f(x2) - f(x1)}{x2 - x1}](https://tex.z-dn.net/?f=%20Average%20rate%20of%20change%20%3D%20%5Cfrac%7Bf%28x2%29%20-%20f%28x1%29%7D%7Bx2%20-%20x1%7D%20)
x2 = 5
x1 = 3
f(x2) = f(5) = 125
f(x1) = f(3) = 27
Thus,
![Average rate of change = \frac{125 - 27}{5 - 3}](https://tex.z-dn.net/?f=%20Average%20rate%20of%20change%20%3D%20%5Cfrac%7B125%20-%2027%7D%7B5%20-%203%7D%20)
![= \frac{98}{2}](https://tex.z-dn.net/?f=%20%3D%20%5Cfrac%7B98%7D%7B2%7D%20)
Average rate of change = 49
Average rate of change of the given table values representing an exponential function is A. 49.