### Randomization Distribution for Hypothesis TestingThe figure below shows a randomization distribution based on 1000 simulated samples for hypotheses \( H_0: \mu_1 = \mu_2 \) vs \( H_a: \mu_1 \neq \mu_2 \). The statistic used for each sample is \( D = \bar{X}_1 - \bar{X}_2 \). Which sample provides the strongest evidence against \( H_0 \)?![Graph showing randomization distribution](image-link)#### Graph Description:- **X-axis (Differences):** Represents the differences (\( D \)) between the sample means, ranging from -3 to 3.- **Y-axis (Frequency):** Represents the frequency of each difference observed in the 1000 simulated samples.- **Distribution Shape:** The distribution is approximately normal, centered around 0, indicating that under the null hypothesis, the differences between the sample means are likely to be close to zero.#### Question:Which sample provides the strongest evidence against \( H_0 \)?- \( D = 2.3 \)- \( D = 1.4 \)- Both provide equally strong evidence against \( H_0 \)**Considerations:** - Larger absolute values of \( D \) indicate stronger evidence against \( H_0 \).- Compare the given \( D \) values to the distribution to determine which is further from the center (0).### Answer:* \( D = 2.3 \) provides the strongest evidence against \( H_0 \).This inference is based on the fact that \( D = 2.3 \) falls further from the center of the distribution compared to \( D = 1.4 \), suggesting it is less likely to occur under the null hypothesis.

Answered: The figure below shows a randomization…

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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