need some help no one can get it right **Hypothesis Testing Educational Exercise**This example will guide you through testing a hypothesis at a significance level of $\alpha = 0.005$, where one dataset represents pre-test scores and the other represents post-test scores.### Hypotheses:- **Null Hypothesis ($H_0$)**: $\mu_d = 0$- **Alternative Hypothesis ($H_a$)**: $\mu_d \ne 0$### Given Data:You believe that the population of difference scores is normally distributed, but the standard deviation is unknown. You obtain pre-test and post-test samples for $ n = 172 $ subjects. The average difference (post - pre) is:- Mean difference, $\bar{d} = -2.3$- Standard deviation of the differences, $s_d = 50.6$### Questions:1. **What is the test statistic for this sample?** - **Answer:** \[ \text{test statistic} = \boxed{\hspace{50pt}} \] (Round to 4 decimal places.)2. **What is the p-value for this sample?** - **Answer:** \[ \text{p-value} = \boxed{\hspace{50pt}} \] (Round to 4 decimal places.)3. **The p-value is:** - $\circ$ less than (or equal to) $\alpha$ - $\circ$ greater than $\alpha$4. **This test statistic leads to a decision to:** - $\circ$ reject the null - $\circ$ accept the null - $\circ$ fail to reject the null5. **As such, the final conclusion is that...** - (Provide your conclusion based on the test results.)This exercise provides practice with the calculation and interpretation of a hypothesis test, crucial for understanding inferential statistics.

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Description: need some help no one can get it right **Hypothesis Testing Educational Exercise**This example will guide you through testing a hypothesis at a significance level of $\alpha = 0.005$, where one dataset represents pre-test scores and the other repre

Answer: Here we will use t-test statistics, as sample standard deviation is given and population…

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Statistics

You wish to test the following claim (Ha) at a significance level of a = 0.005. For the context of this problem, one data set represents a pre-test and the other data set represents a post-test. Ha: Ha + 0 0 = Prt : °H You believe the population of difference scores is normally distributed, but you do not know the standard deviation. You obtain pre-test and post-test samples for n = 172 subjects. The average difference (post - pre) is d = - 2.3 with a standard deviation of the differences of sa = 50.6. a. What is the test statistic for this sample? test statistic = Round to 4 decimal places. b. What is the p-value for this sample? Round to 4 decimal places. p-value = c. The p-value is... O less than (or equal to) a O greater than a d. This test statistic leads to a decision to... O reject the null O accept the null O fail to reject the null e. As such, the final conclusion is that...

You wish to test the following claim (Ha) at a significance level of a = 0.005. For the context of this problem, one data set represents a pre-test and the other data set represents a post-test. Ha: Ha + 0 0 = Prt : °H You believe the population of difference scores is normally distributed, but you do not know the standard deviation. You obtain pre-test and post-test samples for n = 172 subjects. The average difference (post - pre) is d = - 2.3 with a standard deviation of the differences of sa = 50.6. a. What is the test statistic for this sample? test statistic = Round to 4 decimal places. b. What is the p-value for this sample? Round to 4 decimal places. p-value = c. The p-value is... O less than (or equal to) a O greater than a d. This test statistic leads to a decision to... O reject the null O accept the null O fail to reject the null e. As such, the final conclusion is that...

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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Concept explainers

Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.

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need some help no one can get it right

**Hypothesis Testing Educational Exercise**

This example will guide you through testing a hypothesis at a significance level of $\alpha = 0.005$, where one dataset represents pre-test scores and the other represents post-test scores.

### Hypotheses:
- **Null Hypothesis ($H_0$)**: $\mu_d = 0$
- **Alternative Hypothesis ($H_a$)**: $\mu_d \ne 0$

### Given Data:
You believe that the population of difference scores is normally distributed, but the standard deviation is unknown. You obtain pre-test and post-test samples for $ n = 172 $ subjects. The average difference (post - pre) is:

- Mean difference, $\bar{d} = -2.3$
- Standard deviation of the differences, $s_d = 50.6$

### Questions:
1. **What is the test statistic for this sample?**
- **Answer:**
\[
\text{test statistic} = \boxed{\hspace{50pt}}
\]
(Round to 4 decimal places.)

2. **What is the p-value for this sample?**
- **Answer:**
\[
\text{p-value} = \boxed{\hspace{50pt}}
\]
(Round to 4 decimal places.)

3. **The p-value is:**
- $\circ$ less than (or equal to) $\alpha$
- $\circ$ greater than $\alpha$

4. **This test statistic leads to a decision to:**
- $\circ$ reject the null
- $\circ$ accept the null
- $\circ$ fail to reject the null

5. **As such, the final conclusion is that...**
- (Provide your conclusion based on the test results.)

This exercise provides practice with the calculation and interpretation of a hypothesis test, crucial for understanding inferential statistics.

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