6. Suppose you are testing Ho: p= 0.8 H1 : p < 0.8, versus where n = 25. From your data, you calculate your test statistic value as +1.2. (a) Should you use z or t when finding a p-value for this scenario? (b) Calculate the p-value for this scenario. (c) Using a significance level of 0.062, what decision should you make (Reject Ho or Do Not Reject Ho)?
6. Suppose you are testing Ho: p= 0.8 H1 : p < 0.8, versus where n = 25. From your data, you calculate your test statistic value as +1.2. (a) Should you use z or t when finding a p-value for this scenario? (b) Calculate the p-value for this scenario. (c) Using a significance level of 0.062, what decision should you make (Reject Ho or Do Not Reject Ho)?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
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![### Statistical Hypothesis Testing
#### Problem Statement
**6. Suppose you are testing:**
\[ H_0: p = 0.8 \quad \text{versus} \quad H_1: p < 0.8, \]
where \( n = 25 \). From your data, you calculate your test statistic value as \( +1.2 \).
**Tasks:**
(a) Should you use \( z \) or \( t \) when finding a p-value for this scenario?
(b) Calculate the p-value for this scenario.
(c) Using a significance level of 0.062, what decision should you make (Reject \( H_0 \) or Do Not Reject \( H_0 \))?
---
#### Detailed Explanation
- **Test Statistic**: We have a test statistic value of \( +1.2 \).
- **Sample Size \( n \)**: 25.
- **Null Hypothesis \( H_0 \)**: Population proportion \( p = 0.8 \).
- **Alternative Hypothesis \( H_1 \)**: Population proportion \( p < 0.8 \).
- **Significance Level**: 0.062.
---
#### Solution Approach
1. **Choosing Between \( z \) and \( t \):**
- Since we are dealing with proportions and assuming a normal approximation is valid due to reasonable sample size, use the \( z \)-test.
2. **P-value Calculation:**
- Use the standard normal distribution to find the p-value corresponding to a test statistic of \( +1.2 \). Since this is a one-tailed test (because \( H_1: p < 0.8 \)), the p-value is the probability that \( Z > 1.2 \).
3. **Decision Making:**
- Compare the p-value with the significance level (0.062).
- If the p-value is less than the significance level, reject \( H_0 \).
- Otherwise, do not reject \( H_0 \).
Use statistical calculators or tables to determine exact values as needed.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F0393b910-875a-4ed6-a578-5b5396be78bf%2F04ad90a4-4f3c-43ff-9f70-5224f61e6f7c%2F7ox1uxe_processed.png&w=3840&q=75)
Transcribed Image Text:### Statistical Hypothesis Testing
#### Problem Statement
**6. Suppose you are testing:**
\[ H_0: p = 0.8 \quad \text{versus} \quad H_1: p < 0.8, \]
where \( n = 25 \). From your data, you calculate your test statistic value as \( +1.2 \).
**Tasks:**
(a) Should you use \( z \) or \( t \) when finding a p-value for this scenario?
(b) Calculate the p-value for this scenario.
(c) Using a significance level of 0.062, what decision should you make (Reject \( H_0 \) or Do Not Reject \( H_0 \))?
---
#### Detailed Explanation
- **Test Statistic**: We have a test statistic value of \( +1.2 \).
- **Sample Size \( n \)**: 25.
- **Null Hypothesis \( H_0 \)**: Population proportion \( p = 0.8 \).
- **Alternative Hypothesis \( H_1 \)**: Population proportion \( p < 0.8 \).
- **Significance Level**: 0.062.
---
#### Solution Approach
1. **Choosing Between \( z \) and \( t \):**
- Since we are dealing with proportions and assuming a normal approximation is valid due to reasonable sample size, use the \( z \)-test.
2. **P-value Calculation:**
- Use the standard normal distribution to find the p-value corresponding to a test statistic of \( +1.2 \). Since this is a one-tailed test (because \( H_1: p < 0.8 \)), the p-value is the probability that \( Z > 1.2 \).
3. **Decision Making:**
- Compare the p-value with the significance level (0.062).
- If the p-value is less than the significance level, reject \( H_0 \).
- Otherwise, do not reject \( H_0 \).
Use statistical calculators or tables to determine exact values as needed.
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