Determine whether a normal sampling distribution can be used for the following sample statistics. If it can be used, test the claim about the difference between two population proportions p1 and p2at the level of significance α. Assume that the samples are random and independent. Claim: p1≠p2, α=0.01Sample Statistics:x1=36,n1=75,x2=38,n2=65 Determine whether a normal sampling distribution can be used. The samples are random and independent. A normal sampling distribution cannotcanbe used becausen1p=enter your response here,n1q=enter your response here,n2p=enter your response here,andn2q=enter your response here.(Round to two decimal places as needed.)State the null and alternative hypotheses, if applicable. A.H0:p1=p2Ha:p1≠p2 B.H0:p1≤p2Ha:p1>p2 C.H0:p1≥p2Ha:p1<p2 D.The conditions to use a normal sampling distribution are not met.Calculate the standardized test statistic for the differencep1−p2,if applicable. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. A.z=enter your response here(Round to two decimal places as needed.) B.The conditions to use a normal sampling distribution are not met.Calculate the P-value, if applicable. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. A.P=enter your response here(Round to three decimal places as needed.) B.The conditions to use a normal sampling distribution are not met.State the conclusion of the hypothesis test, if applicable. Choose the correct answer below. A.SinceP>α,rejectH0.Thereisenough evidence at theα=0.01level of significance to support the claim. B.SinceP>α,fail to rejectH0.Thereis notenough evidence at theα=0.01level of significance to support the claim. C.SinceP<α,fail to rejectH0.Thereis notenough evidence at theα=0.01level of significance to support the claim. D.SinceP<α,rejectH0.Thereisenough evidence at theα=0.01level of significance to support the claim. E.The conditions to use a normal sampling distribution are not met.

The random variable X follows binomial distribution. There are two independent samples. We have to…

Determine whether a normal sampling distribution can be used for the following sample statistics. If it can be used, test the claim about the difference between two population proportions p1 and p2 at the level of significance α. Assume that the samples are random and independent. Claim: p1≠p2, α=0.01 Sample Statistics: x1=36, n1=75, x2=38, n2=65 Determine whether a normal sampling distribution can be used. The samples are random and independent. A normal sampling distribution cannot can be used because n1p=enter your response here, n1q=enter your response here, n2p=enter your response here, and n2q=enter your response here. (Round to two decimal places as needed.) State the null and alternative hypotheses, if applicable. A. H0: p1=p2 Ha: p1≠p2 B. H0: p1≤p2 Ha: p1>p2 C. H0: p1≥p2 Ha: p1α, reject H0. There is enough evidence at the α=0.01 level of significance to support the claim. B. Since P>α, fail to reject H0. There is not enough evidence at the α=0.01 level of significance to support the claim. C. Since P<α, fail to reject H0. There is not enough evidence at the α=0.01 level of significance to support the claim. D. Since P<α, reject H0. There is enough evidence at the α=0.01 level of significance to support the claim. E. The conditions to use a normal sampling distribution are not met.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

Determine whether a normal sampling distribution can be used for the following sample statistics. If it can be used, test the claim about the difference between two population proportions p1 and p2
at the level of significance α. Assume that the samples are random and independent. Claim: p1≠p2, α=0.01

Sample Statistics:

x1=36,

n1=75,

x2=38,

n2=65

Determine whether a normal sampling distribution can be used.

The samples are random and independent. A normal sampling distribution

cannot

can

be used because

n1p=enter your response here,

n1q=enter your response here,

n2p=enter your response here,

and

n2q=enter your response here.

(Round to two decimal places as needed.)

State the null and alternative hypotheses, if applicable.

H0:

p1=p2

Ha:

p1≠p2

H0:

p1≤p2

Ha:

p1>p2

H0:

p1≥p2

Ha:

p1<p2

The conditions to use a normal sampling distribution are not met.

Calculate the standardized test statistic for the difference

p1−p2,

if applicable. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.

z=enter your response here

(Round to two decimal places as needed.)

The conditions to use a normal sampling distribution are not met.

Calculate the P-value, if applicable. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.

P=enter your response here

(Round to three decimal places as needed.)

The conditions to use a normal sampling distribution are not met.

State the conclusion of the hypothesis test, if applicable. Choose the correct answer below.

Since

P>α,

reject

H0.

There

enough evidence at the

α=0.01

level of significance to support the claim.

Since

P>α,

fail to reject

H0.

There

is not

enough evidence at the

α=0.01

level of significance to support the claim.

Since

P<α,

fail to reject

H0.

There

is not

enough evidence at the

α=0.01

level of significance to support the claim.

Since

P<α,

reject

H0.

There

enough evidence at the

α=0.01

level of significance to support the claim.

The conditions to use a normal sampling distribution are not met.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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