A random sample of n = 1,000 observations from a binomial population contained 328 successes. You wish to show that p < 0.35. n = 1,000 and x = 328. You wish to show that p < 0.35. In USE SALT Calculate the appropriate test statistic. (Round your answer to two decimal places.) z = Calculate the p-value. (Round your answer to four decimal places.) p-value = Do the conclusions based on a fixed rejection region of z < -1.645 agree with those found using the p-value approach at a = 0.05? Yes, both approaches produce the same conclusion. No, the p-value approach rejects the null hypothesis when the fixed rejection region approach fails to reject the null hypothesis. No, the fixed rejection region approach rejects the null hypothesis when the p-value approach fails to reject the null hypothesis. Should they? O Yes No
A random sample of n = 1,000 observations from a binomial population contained 328 successes. You wish to show that p < 0.35. n = 1,000 and x = 328. You wish to show that p < 0.35. In USE SALT Calculate the appropriate test statistic. (Round your answer to two decimal places.) z = Calculate the p-value. (Round your answer to four decimal places.) p-value = Do the conclusions based on a fixed rejection region of z < -1.645 agree with those found using the p-value approach at a = 0.05? Yes, both approaches produce the same conclusion. No, the p-value approach rejects the null hypothesis when the fixed rejection region approach fails to reject the null hypothesis. No, the fixed rejection region approach rejects the null hypothesis when the p-value approach fails to reject the null hypothesis. Should they? O Yes No
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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![A random sample of \( n = 1,000 \) observations from a binomial population contained 328 successes. You wish to show that \( p < 0.35 \).
\( n = 1,000 \) and \( x = 328 \). You wish to show that \( p < 0.35 \).
**Calculate the appropriate test statistic. (Round your answer to two decimal places.)**
\( z = \) [__________]
**Calculate the \( p \)-value. (Round your answer to four decimal places.)**
\( p\text{-value} = \) [__________]
**Do the conclusions based on a fixed rejection region of \( z < -1.645 \) agree with those found using the \( p \)-value approach at \( \alpha = 0.05 \)?**
- \( \bigcirc \) Yes, both approaches produce the same conclusion.
- \( \bigcirc \) No, the \( p \)-value approach rejects the null hypothesis when the fixed rejection region approach fails to reject the null hypothesis.
- \( \bigcirc \) No, the fixed rejection region approach rejects the null hypothesis when the \( p \)-value approach fails to reject the null hypothesis.
**Should they?**
- \( \bigcirc \) Yes
- \( \bigcirc \) No](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7104469d-fb7e-48cd-bb9c-a2d8cb607855%2F12df2140-f296-4783-8d44-f227c91a04e1%2F960pogt_processed.png&w=3840&q=75)
Transcribed Image Text:A random sample of \( n = 1,000 \) observations from a binomial population contained 328 successes. You wish to show that \( p < 0.35 \).
\( n = 1,000 \) and \( x = 328 \). You wish to show that \( p < 0.35 \).
**Calculate the appropriate test statistic. (Round your answer to two decimal places.)**
\( z = \) [__________]
**Calculate the \( p \)-value. (Round your answer to four decimal places.)**
\( p\text{-value} = \) [__________]
**Do the conclusions based on a fixed rejection region of \( z < -1.645 \) agree with those found using the \( p \)-value approach at \( \alpha = 0.05 \)?**
- \( \bigcirc \) Yes, both approaches produce the same conclusion.
- \( \bigcirc \) No, the \( p \)-value approach rejects the null hypothesis when the fixed rejection region approach fails to reject the null hypothesis.
- \( \bigcirc \) No, the fixed rejection region approach rejects the null hypothesis when the \( p \)-value approach fails to reject the null hypothesis.
**Should they?**
- \( \bigcirc \) Yes
- \( \bigcirc \) No
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