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)?

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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.
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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