Answer:
B.254.34 in.2
Step-by-step explanation:
Answer:
P(Y ≥ 15) = 0.763
Step-by-step explanation:
Given that:
Mean =135
standard deviation = 12
sample size n = 50
sample mean
= 140
Suppose X is the random variable that follows a normal distribution which represents the weekly supermarket expenses
Then,
![X \sim N ( \mu \sigma)](https://tex.z-dn.net/?f=X%20%5Csim%20N%20%28%20%5Cmu%20%5Csigma%29)
The probability that X is greater than 140 is :
P(X>140) = 1 - P(X ≤ 140)
![P(X>140) = 1 - P( \dfrac{X-\mu}{\sigma} \leq \dfrac{140-135}{12})](https://tex.z-dn.net/?f=P%28X%3E140%29%20%3D%201%20-%20P%28%20%5Cdfrac%7BX-%5Cmu%7D%7B%5Csigma%7D%20%5Cleq%20%5Cdfrac%7B140-135%7D%7B12%7D%29)
![P(X>140) = 1 - P( \dfrac{X-\mu}{\sigma} \leq \dfrac{5}{12})](https://tex.z-dn.net/?f=P%28X%3E140%29%20%3D%201%20-%20P%28%20%5Cdfrac%7BX-%5Cmu%7D%7B%5Csigma%7D%20%5Cleq%20%5Cdfrac%7B5%7D%7B12%7D%29)
![P(X>140) = 1 - P( Z\leq0.42)](https://tex.z-dn.net/?f=P%28X%3E140%29%20%3D%201%20-%20P%28%20Z%5Cleq0.42%29)
From z tables,
![P(X>140) = 1 - 0.6628](https://tex.z-dn.net/?f=P%28X%3E140%29%20%3D%201%20-%200.6628)
![P(X>140) = 0.3372](https://tex.z-dn.net/?f=P%28X%3E140%29%20%3D%200.3372)
Similarly, let consider Y to be the variable that follows a binomial distribution of the no of household whose expense is greater than $140
Then;
![Y \sim Binomial (np)](https://tex.z-dn.net/?f=Y%20%5Csim%20Binomial%20%28np%29)
![Y \sim Binomial (50,0.3372)](https://tex.z-dn.net/?f=Y%20%5Csim%20Binomial%20%2850%2C0.3372%29)
∴
P(Y ≥ 15) = 1- P(Y< 15)
P(Y ≥ 15) = 1 - ( P(Y=0) + P(Y=1) + P(Y=2) + ... + P(Y=14) )
![P(Y \geq 15) = 1 - \begin {pmatrix} ^{50}_0 \end {pmatrix} (0.3372)^0 (1-0,3372)^{50} + \begin {pmatrix} ^{50}_1 \end {pmatrix} (0.3372)^1 (1-0,3372)^{49} + \begin {pmatrix} ^{50}_2 \end {pmatrix} (0.3372)^2 (1-0,3372)^{48} +... + \begin {pmatrix} ^{50}_{50{ \end {pmatrix} (0.3372)^{50} (1-0,3372)^{0}](https://tex.z-dn.net/?f=P%28Y%20%5Cgeq%2015%29%20%3D%201%20-%20%5Cbegin%20%7Bpmatrix%7D%20%5E%7B50%7D_0%20%5Cend%20%7Bpmatrix%7D%20%280.3372%29%5E0%20%281-0%2C3372%29%5E%7B50%7D%20%2B%20%5Cbegin%20%7Bpmatrix%7D%20%5E%7B50%7D_1%20%5Cend%20%7Bpmatrix%7D%20%280.3372%29%5E1%20%281-0%2C3372%29%5E%7B49%7D%20%20%2B%20%5Cbegin%20%7Bpmatrix%7D%20%5E%7B50%7D_2%20%5Cend%20%7Bpmatrix%7D%20%280.3372%29%5E2%20%281-0%2C3372%29%5E%7B48%7D%20%2B...%20%20%2B%20%5Cbegin%20%7Bpmatrix%7D%20%5E%7B50%7D_%7B50%7B%20%5Cend%20%7Bpmatrix%7D%20%280.3372%29%5E%7B50%7D%20%281-0%2C3372%29%5E%7B0%7D)
P(Y ≥ 15) = 0.763
X= 45
z=45
y=90
180-135 is 45 degrees for Z. X is also 45 while y then becomes 90. as 90+45+45=180.
Answer:
Not sure sorry
Step-by-step explanation:
Answer:
Option B) Reject null hypothesis
Step-by-step explanation:
We are given the following in the question:
We are given the null hypothesis:
![H_0 = 4,000](https://tex.z-dn.net/?f=H_0%20%3D%204%2C000)
![\alpha = 0.01](https://tex.z-dn.net/?f=%5Calpha%20%3D%200.01)
![z_{stat} = 6.00](https://tex.z-dn.net/?f=z_%7Bstat%7D%20%3D%206.00)
Two tailed z-test
Now, ![z_{critical} \text{ at 0.01 level of significance } = \pm 2.58](https://tex.z-dn.net/?f=z_%7Bcritical%7D%20%5Ctext%7B%20at%200.01%20level%20of%20significance%20%7D%20%3D%20%5Cpm%202.58)
Since,
The calculated z-statistic does not lie in the acceptance region, we fail to accept and reject the null hypothesis.
Left-tailed z-test
Now, ![z_{critical} \text{ at 0.01 level of significance } = -2.58](https://tex.z-dn.net/?f=z_%7Bcritical%7D%20%5Ctext%7B%20at%200.01%20level%20of%20significance%20%7D%20%3D%20-2.58)
Since,
![z_{stat} > z_{critical}](https://tex.z-dn.net/?f=z_%7Bstat%7D%20%3E%20z_%7Bcritical%7D)
We fail to accept and reject the null hypothesis.
Right-tailed z-test
Now, ![z_{critical} \text{ at 0.01 level of significance } = 2.58](https://tex.z-dn.net/?f=z_%7Bcritical%7D%20%5Ctext%7B%20at%200.01%20level%20of%20significance%20%7D%20%3D%202.58)
Since,
![z_{stat} > z_{critical}](https://tex.z-dn.net/?f=z_%7Bstat%7D%20%3E%20z_%7Bcritical%7D)
We fail to accept and reject the null hypothesis.