Answer:
50 is correct
Step-by-step explanation:
did my math but I know you need it quick so sorry for brief answer
<h2>
Answer:</h2>
.
<h2>
Step-by-step explanation:</h2>
<h3>1. Write the expression.</h3>
![y=14x^2](https://tex.z-dn.net/?f=y%3D14x%5E2)
<h3>2. Substitute y for x, and x for y.</h3>
![x=14y^{2}](https://tex.z-dn.net/?f=x%3D14y%5E%7B2%7D)
<h3>3. Solve for y.</h3>
![14y^{2}=x\\ \\y^{2} =\frac{x}{14} \\ \\y=\sqrt{\frac{x}{14}}](https://tex.z-dn.net/?f=14y%5E%7B2%7D%3Dx%5C%5C%20%5C%5Cy%5E%7B2%7D%20%3D%5Cfrac%7Bx%7D%7B14%7D%20%5C%5C%20%5C%5Cy%3D%5Csqrt%7B%5Cfrac%7Bx%7D%7B14%7D%7D)
<h3>4. Express your result.</h3>
.
Answer:
No. we cannot believe it as per hypothesis test done.
Step-by-step explanation:
Given that five hundred draws are made at random with replacement from a box of numbered tickets; 276 are positive.
To test the claim whether the proportion for positive numbers is 50% let us conduct a hypothesis test for proportions.
![H_0: p =0.5\\H_a: p\neq 0.5](https://tex.z-dn.net/?f=H_0%3A%20p%20%3D0.5%5C%5CH_a%3A%20p%5Cneq%200.5)
(Two tailed test at 5% significance level)
Sample proportion p = ![\frac{276}{500} =0.552](https://tex.z-dn.net/?f=%5Cfrac%7B276%7D%7B500%7D%20%3D0.552)
Std error of p = ![\sqrt{\frac{P(1-P)}{500} } \\=0.02236](https://tex.z-dn.net/?f=%5Csqrt%7B%5Cfrac%7BP%281-P%29%7D%7B500%7D%20%7D%20%5C%5C%3D0.02236)
(assuming null hypothesis to be true)
Here P = 0.50
Test statistic = p difference/std error = ![\frac{0.052}{0.02236} \\=2.33](https://tex.z-dn.net/?f=%5Cfrac%7B0.052%7D%7B0.02236%7D%20%5C%5C%3D2.33)
Z test is used for this proportion.
p value = 0.0198
Since p value <0.05 we reject null hypothesis
At 95% confidence level, there is statistical evidence to show that sample mean is not 50%
Answer:
7
Step-by-step explanation:
28 35 56
1 and 28 1 and 35 1 and 56
2 and 14 7 and 5 2 and 28
4 and 7 4 and 14
7 and 8