For study results to be meaningful, it is important to ensure that there are no erroneous imbalances in the data that could lead the researcher to a false conclusion
Statistical Practice: Chi-square Testing
For study results to be meaningful, it is important to ensure that there are no erroneous imbalances in the data that could lead the researcher to a false conclusion. A properly designed study should anticipate where such imbalances might occur and attempt to avoid them through careful planning. In this scenario, we will assume that the study was well planned, but due to circumstances beyond the control of the researcher, some of the recruited participants did not finish the study. The researcher is concerned that there may be an imbalance in the number of male and female groups receiving the standard or vegetarian diet treatment. If there are not enough males relative to the females in the vegetarian treatment group, the results may be misleading.
Instructions
For this discussion, use the Alaska study’s Emotional Well-Being data set to perform the chi-square test of independence on the variables Gender and Dietary Treatment.
The chi-square test will help determine if there is a gender imbalance in the data set. Although this chi-square test is considered fairly easy to understand and perform, you may find it useful to find other how-to videos on the Internet. Feel free to share anything you have found to be particularly enlightening.
For your initial post, refer to the guidelines in the FEM as you complete the following:
Describe, in your own words, when to use the chi-square test of independence.
Using the Emotional Well-Being data set linked in Resources, report the results of the chi-square test of independence that you perform.
Based on the results, provide a 1-2 sentence practical interpretation.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
Addressthe following in your response:
How do the interpretations ofyour peers compare to yours?
Learning Components
This activity will help you achieve the following learning components:
Identify a normal distribution assumption test for two variables.
Perform a normal distribution assumption test for two variables to determine if data is normally distributed.
Identify an appropriate correlation test to determine the direction and strength of the relationship of two variables.
Perform an appropriate correlation test to determine the direction and strength or magnitude of the relationship between two variables.
Interpret the effect size for correlation analysis results.
Resources
Discussion Participation Scoring Guide.
Emotional Well-Being (SF-36) Study Data Set [XLSX].
DQ2 Critiquing Public Health Literature Reporting: Quantitative Data
For this discussion, we will continue the same process we used in Unit 6, when we collaboratively analyzed a public health study. We will examine the Schwendimann et al. study linked in Resources and ask the same type of questions as before. TheRothman, Montori, Cherrington, and Pignone article may be useful if you need help articulating specific numerical data observations.
Instructions?
?Read or review the article on fall preventionby Schwendimann, Milisen,Bühler, and De Geest.
For your initial post, refer to the guidelines in the FEM and the linked Resourcesas you address the following:
Identify the study’s target population.
Describe the specific problem that prompted the authors to do this study.
Describe the intervention, citing at least one previous study used in the article to justify the intervention. Locate the article to find supporting efficacy data.
Describe all the instruments the authors used to show the efficacy of their intervention.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
Address the following in your response:
How do the analyses of your peers compare to yours?
Resources
Discussion Participation Scoring Guide.
APA Module.
Capella University Library.
Fall Prevention in a Swiss Acute Care Hospital Setting.
Perspective: The Role of Numeracy in Health Care.
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