Do the following for the specified one-mean t-test. a. Use a t-table to estimate the P-value. b. Based on your estimate in part (a), state at which significance levels the null hypothesis can be rejected, at which significance levels it cannot be rejected, and at which significance levels it is not possible to decide. Left-tailed test, n= 11, and t= -2.074

MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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**Instructions for Performing a One-Sample t-Test:**

1. **Use a t-table to estimate the P-value:**
   - Given details: Left-tailed test, sample size \( n = 11 \), and test statistic \( t = -2.074 \).

   - Guidance is provided to view page 1 and page 2 of the t-table for more details.

2. **Estimating the P-value:**
   - The P-value is determined to be between 0.025 and 0.05.

3. **Decision-making based on significance levels:**
   - **Rejection and Non-rejection of the Null Hypothesis (\( H_0 \)):**
     - Rejection: \( H_0 \) can be rejected for significance level selections as \( \alpha \leq 0.05 \).
     - Non-rejection: \( H_0 \) cannot be rejected for significance levels higher than this threshold unless specified.
     - For certain significance levels, the t-table might not provide enough detail to decide on rejecting \( H_0 \).

4. **Dropdown Options:**
   - The dropdown menus provide various significance levels (\( \alpha \)) for selection, such as \( \alpha \geq 0.01 \), \( \alpha \leq 0.025 \), \( \alpha \leq 0.05 \), etc., which help in determining the specific conditions under which \( H_0 \) can or cannot be rejected.

This exercise is designed to help students understand how to utilize a t-table for estimating P-values and making decisions regarding hypotheses in statistical tests.
Transcribed Image Text:**Instructions for Performing a One-Sample t-Test:** 1. **Use a t-table to estimate the P-value:** - Given details: Left-tailed test, sample size \( n = 11 \), and test statistic \( t = -2.074 \). - Guidance is provided to view page 1 and page 2 of the t-table for more details. 2. **Estimating the P-value:** - The P-value is determined to be between 0.025 and 0.05. 3. **Decision-making based on significance levels:** - **Rejection and Non-rejection of the Null Hypothesis (\( H_0 \)):** - Rejection: \( H_0 \) can be rejected for significance level selections as \( \alpha \leq 0.05 \). - Non-rejection: \( H_0 \) cannot be rejected for significance levels higher than this threshold unless specified. - For certain significance levels, the t-table might not provide enough detail to decide on rejecting \( H_0 \). 4. **Dropdown Options:** - The dropdown menus provide various significance levels (\( \alpha \)) for selection, such as \( \alpha \geq 0.01 \), \( \alpha \leq 0.025 \), \( \alpha \leq 0.05 \), etc., which help in determining the specific conditions under which \( H_0 \) can or cannot be rejected. This exercise is designed to help students understand how to utilize a t-table for estimating P-values and making decisions regarding hypotheses in statistical tests.
**b.** We can reject \( H_0 \) for \(\_\_\_\_\_\), and we cannot reject \( H_0 \) for \(\_\_\_\_\_\). For significance levels \(\_\_\_\_\_\), the t-table is not sufficiently detailed in order to decide whether to reject \( H_0 \).

There is a dropdown menu available with the following options:

- \(0.05 < \alpha < 0.10\)
- \(0.025 < \alpha < 0.05\)
- \(0.01 < \alpha < 0.025\)
- \(0.005 < \alpha < 0.01\)
Transcribed Image Text:**b.** We can reject \( H_0 \) for \(\_\_\_\_\_\), and we cannot reject \( H_0 \) for \(\_\_\_\_\_\). For significance levels \(\_\_\_\_\_\), the t-table is not sufficiently detailed in order to decide whether to reject \( H_0 \). There is a dropdown menu available with the following options: - \(0.05 < \alpha < 0.10\) - \(0.025 < \alpha < 0.05\) - \(0.01 < \alpha < 0.025\) - \(0.005 < \alpha < 0.01\)
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