**Title: Understanding Statistical Power****A statistical power of 95% implies that:**- ☐ the chance that the alternative hypothesis is true is 95%.- ☐ the p-value for the study will be 5%.- ☐ $H_0$ is probably false.- ☑ it is very likely that $H_0$ will be rejected if it is not true.**Explanation:**Statistical power is the probability that a test will reject a false null hypothesis ($H_0$). A 95% power indicates that there is a 95% chance of correctly rejecting $H_0$ when it is indeed false. Power is primarily a function of the significance level, sample size, and effect size.[Submit Question Button]

Power is the probability of rejecting null hypothesis when null hypothesis is false and power is…

A statistical power of 95% implies that O the chance that the alternative hypothesis is true is 95%. O the p-value for the study will be 5%. O Ho is probably false. O it is very likely that Ho will be rejected if it is not true.

A statistical power of 95% implies that O the chance that the alternative hypothesis is true is 95%. O the p-value for the study will be 5%. O Ho is probably false. O it is very likely that Ho will be rejected if it is not true.

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

Estimation

A new framework of data analysis where the new statistical methods are used for interpreting the results and analyzing the data is known as estimation in statistics.

Question

**Title: Understanding Statistical Power**

**A statistical power of 95% implies that:**

- ☐ the chance that the alternative hypothesis is true is 95%.
- ☐ the p-value for the study will be 5%.
- ☐ $H_0$ is probably false.
- ☑ it is very likely that $H_0$ will be rejected if it is not true.

**Explanation:**

Statistical power is the probability that a test will reject a false null hypothesis ($H_0$). A 95% power indicates that there is a 95% chance of correctly rejecting $H_0$ when it is indeed false. Power is primarily a function of the significance level, sample size, and effect size.

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