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You must install the jpower module in Jamovi. To install this module, click the + Modules button in the upper right corner then select jamovi library. Scroll through the module options until you see jpower and click install. Once installed, click the jpower module and select the Independent Sample T-Test option. I. For power = 0.55, required n =

You must install the jpower module in Jamovi. To install this module, click the + Modules button in the upper right corner then select jamovi library. Scroll through the module options until you see jpower and click install. Once installed, click the jpower module and select the Independent Sample T-Test option. I. For power = 0.55, required n =

MATLAB: An Introduction with Applications
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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Suppose a study is being planned that will investigate whether female Beagles with severe periodontitis (gum and mouth disease) give birth to smaller litters of puppies, on average, than Beagles without periodontitis. Based on previous research, the standard deviation of litter size is estimated to be 2.1 puppies.

Suppose we suspect that Beagles with periodontitis will give birth to on average 6 puppies whereas Beagles without periodontitis will give birth to on average 5 puppies. 

 

c. Let's assume that population effect size is Cohen's d = 0.5 (in practice the population effect size is unknown, so we use a value for an effect size we'd be interested in discovering). For each value of desired power, find the total sample size (i.e. the sample size for both groups combined) required to detect this effect. You must instail the jpower module in Jamovi. To install this module, click the + Modules button in the upper right corner then select jamovi library. Scroll through the module options until you see jpower and click install. Once installed, click the jpower module and select the Independent Sample T-Test option. i. For power = 0.55, required n = ii. For power = 0.7, required n = iii. For power = 0.9, required n = d. Now let's see what happens to these calculations if we assume the effect size is a little bit larger. Using d = 0.6, re-do the calculations from part c. above: i. For power = 0.55, required n = ii. For power = 0.7, required n = iii. For power = 0.9, required n = e. Now suppose that the sample size available to you is fixed. In this case, the main interest is finding out what your power will be, given sample size. Find the power of the test for each combination of effect size and total sample size below (remember, when entering sample sizes into jamovi, you are entering the sample size for one group), and round your answers to three decimal places. Assuming effect size = 0.5: i. When total n = 6, power = ii. When total n = 30, power = ii, When total n = 80, power = For effect size = 0.8: i. When total n = 6, power = ii. When total n = 30, power = iji, When total n = 80, power = f. Suppose it turns out that the true population effect size is much smaller than we thought, e.g. d = 0.1. Also suppose we use a small sample size, e.g. n = 20. which of the following should be true? Select all that apply. We will probably reject HO - We will probably fail to reject HO We will probably commit a Type I error We will probably commit a Type II error In order to detect a "significant" difference, we will have to underestimate the true difference in mean litter sizes In order to detect a "significant" difference, we will have to overestimate the true difference in mean litter sizes
Transcribed Image Text:c. Let's assume that population effect size is Cohen's d = 0.5 (in practice the population effect size is unknown, so we use a value for an effect size we'd be interested in discovering). For each value of desired power, find the total sample size (i.e. the sample size for both groups combined) required to detect this effect. You must instail the jpower module in Jamovi. To install this module, click the + Modules button in the upper right corner then select jamovi library. Scroll through the module options until you see jpower and click install. Once installed, click the jpower module and select the Independent Sample T-Test option. i. For power = 0.55, required n = ii. For power = 0.7, required n = iii. For power = 0.9, required n = d. Now let's see what happens to these calculations if we assume the effect size is a little bit larger. Using d = 0.6, re-do the calculations from part c. above: i. For power = 0.55, required n = ii. For power = 0.7, required n = iii. For power = 0.9, required n = e. Now suppose that the sample size available to you is fixed. In this case, the main interest is finding out what your power will be, given sample size. Find the power of the test for each combination of effect size and total sample size below (remember, when entering sample sizes into jamovi, you are entering the sample size for one group), and round your answers to three decimal places. Assuming effect size = 0.5: i. When total n = 6, power = ii. When total n = 30, power = ii, When total n = 80, power = For effect size = 0.8: i. When total n = 6, power = ii. When total n = 30, power = iji, When total n = 80, power = f. Suppose it turns out that the true population effect size is much smaller than we thought, e.g. d = 0.1. Also suppose we use a small sample size, e.g. n = 20. which of the following should be true? Select all that apply. We will probably reject HO - We will probably fail to reject HO We will probably commit a Type I error We will probably commit a Type II error In order to detect a "significant" difference, we will have to underestimate the true difference in mean litter sizes In order to detect a "significant" difference, we will have to overestimate the true difference in mean litter sizes
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