You wish to test the following claim (Ha) at a significance level of α=0.002 Ho:p=0.14 Ha:p>0.14You obtain a sample of size n=241n=241 in which there are 42 successful observations. For this test, you should NOT use the continuity correction, and you should use the normal distribution as an approximation for the binomial distribution.What is the test statistic for this sample? (Report answer accurate to two decimal places.)test statistic = What is the PP-value for this sample? (Report answer accurate to four decimal places.)PP-value = The PP-value is: choose one of two possible answersless than (or equal to) ααgreater than ααThis test statistic leads to a decision to: choose one of three possible answers.reject the nullaccept the nullfail to reject the nullAs such, the final conclusion is that: choose one of four possible answers.There is sufficient evidence to warrant rejection of the claim that the population proportion is greater than 0.14.There is not sufficient evidence to warrant rejection of the claim that the population proportion is greater than 0.14.The sample data support the claim that the population proportion is greater than 0.14.There is not sufficient sample evidence to support the claim that the population proportion is greater than 0.14.

Name: You wish to test the following claim (Ha) at a significance level of α
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Description: You wish to test the following claim (Ha) at a significance level of α=0.002 Ho:p=0.14 Ha:p>0.14You obtain a sample of size n=241n=241 in which there are 42 successful observations. For this test, you should NOT use the continuity correctio

From provided information, it is claimed that proportion is greater than 0.14 Hypotheses can be constructed as: H0: p=0.14Ha: p>0.14 Data is: n=241 and there are 42 successful observations i.e. x=42 p̂=x/n= 0.1743Test statistic can be obtained as: z=p^-pp1-pn=0.1743-0.140.141-0.14241=1.5334 Thus, test statistic is 1.53.The test is one tailed. The p value of the test statistic from the standard normal table is 0.0626 The level of significance (α) = 0.002 Decision rule: Reject H0: if p value < level of significance (α) Since, the p value is 0.0626 which is greater than level of significance (α), therefore, the null hypothesis would be failed reject and it can be concluded that there is not sufficient sample evidence to support the claim that the population proportion is greater than 0.14.

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

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You wish to test the following claim (Ha) at a significance level of α=0.002

Ho:p=0.14
Ha:p>0.14

You obtain a sample of size n=241n=241 in which there are 42 successful observations. For this test, you should NOT use the continuity correction, and you should use the normal distribution as an approximation for the binomial distribution.

What is the test statistic for this sample? (Report answer accurate to two decimal places.)
test statistic =

What is the PP-value for this sample? (Report answer accurate to four decimal places.)
PP-value =

The PP-value is: choose one of two possible answers

less than (or equal to) αα
greater than αα

This test statistic leads to a decision to: choose one of three possible answers.

reject the null
accept the null
fail to reject the null

As such, the final conclusion is that: choose one of four possible answers.

There is sufficient evidence to warrant rejection of the claim that the population proportion is greater than 0.14.
There is not sufficient evidence to warrant rejection of the claim that the population proportion is greater than 0.14.
The sample data support the claim that the population proportion is greater than 0.14.
There is not sufficient sample evidence to support the claim that the population proportion is greater than 0.14.

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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