# Develop effective and ethical approaches for sampling and data collection and justify the choices.

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Sample Size

Overview

In this assignment, you will use the G*Power application. By successfully completing this assignment, you will demonstrate your proficiency in the following course competencies:

· Develop effective and ethical approaches for sampling and data collection and justify the choices.

· Communicate quantitative methodologies, results, analysis, and conclusions effectively.

Step 1: Determine and Understand Statistical Power

In this first step, you will explore how three levels of statistical power influence the sample size for a linear multiple regression.

1. Open G*Power and select F-Tests and Linear multiple regression, fixed model, R2 deviation from zero. Select A priori: Compute sample size given alpha, power, and effect size.

2. Move your mouse over the box to the right of Effect size f2. Notice how a window opens providing you values for small, medium, and large effect sizes. Select the value 0.15 for a medium effect size.

3. Enter 0.05 for the alpha error probability.

4. Enter 2 for the number of predictors. The predictors are the independent variables to be entered simultaneously into the regression. In this case, to determine the simultaneous effect, it means that you have two independent variables.

5. Leave the above settings the same while you compute the sample sizes for three statistical power levels of .8, .9, and .95. Enter each of these values in the Power box, click Calculate, then perform these steps:

1. For each sample size computation, go to the top of the G*Power window and click Protocol of power analysis.

2. Then, copy and paste the contents in the window into your Word document. Make note of the Total Sample Size that G*Power indicates is needed to achieve the selected power level.

6. Notice how the sample size changed as the desired statistical power was increased. Describe these changes and how this influences the choice of a statistical power level for an a priori sample size determination.

Step 2: Determine and Understand Statistical Significance

In this next step, you will explore how three levels of statistical significance influence the sample size for a linear multiple regression.

1. Open G*Power and select F-Tests and Linear multiple regression, fixed model, R2 deviation from zero. Select A priori: Compute sample size given alpha, power, and effect size.

2. Enter a value for a medium effect size, 0.15 for the Effect size f2 box.

3. Enter 2 for the number of predictors. The predictors are the independent variables that will be entered simultaneously into the regression. In this case, to determine the simultaneous effect, it means that you have two independent variables.

4. Enter a value of 0.8 in the Power box.

5. Leave the above settings the same while you compute the sample sizes for three different values of Alpha Error Probability: Use 0.05, 0.01, and 0.001 as your three values, click Calculate, and perform these steps:

1. For each sample size computation, go to the top of the G*Power window and click Protocol of power analysis.

2. Then, copy and paste the contents in the window into your Word document. Make note of the Total Sample Size that G*Power indicates is needed to achieve the selected alpha level.

6. Notice how the sample size changed as the required alpha level of statistical significance was increased. Describe the changes and how this influences the choice of a statistical significance level for an a priori sample size determination.

Step 3: Determine and Understand Effect Size

In this step, you will explore how three levels of effect size influence the sample size for a linear multiple regression.

1. Open G*Power and select F-Tests and Linear multiple regression, fixed model, R2 deviation from zero. Select A priori: Compute sample size given alpha, power, and effect size.

2. Enter 0.05 for the alpha error probability.

3. Enter 2 for the number of predictors. The predictors are the independent variables that will be entered simultaneously into the regression. In this case, to determine the simultaneous effect, it means that you have two independent variables.

4. Enter a value of 0.8 in the Power box.

5. Leave the above settings the same while you compute the sample sizes for three different values of Effect size f2. Use 0.02, 0.15, and 0.35 as your three values for small, medium, and large required effect sizes respectively, click Calculate, and then perform these steps:

1. For each sample size computation, go to the top of the G*Power window and click Protocol of power analysis.

2. Copy and paste the contents in the window into your Word document. Make note of the Total Sample Size that G*Power indicates is needed to achieve the selected effect size.

6. Notice how the sample size changed as the effect level was increased. Describe the changes and how this influences the choice of an effect size for an a priori sample size determination.

Step 4: Report

1. Create an APA-formatted report detailing Steps 1–3 in that order.

2. Use section headings that match the labels on Steps 1, 2, and 3. Use subsection headings for each major substep. Make sure you include a cover page with the appropriate information, including your name.

3. Support your discussion with credible research methods references (such as Field, 2018) and include an APA-formatted reference list of all sources cited in the report.

4. Refer to the assignment scoring guide to ensure that you meet all criteria.

5. Save your report as YourLastName_U3.doc and submit it to the Unit 3 assignment.

Scoring Guide

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