Psy 223 Milestone Two Guidelines And Rubric

Psy 223 Milestone Two Guidelines And Rubric In This Milestone You

Indicate the sample size (n = ?), and describe what consequence(s) this sample size will have in terms of analyses and reporting.

Using the Choose Your Test document, select a statistical procedure appropriate to your scenario/data. Explain why you selected that test, linking features of the scenario/data to information from the Choose Your Test document.

Paper For Above instruction

The process of designing and analyzing research studies hinges significantly on understanding the sample size and selecting appropriate statistical procedures that align with the research questions and data characteristics. In this paper, I will discuss the sample size chosen for my study, how this size influences analysis and reporting, and the rationale behind selecting a specific statistical test suitable for my data scenario.

Sample Size (n) and Its Implications

For my research, I have determined a sample size of n = 50 participants. This size strikes a balance between feasibility and statistical power, which pertains to the probability of correctly rejecting a false null hypothesis. A sample of this size generally provides sufficient power to identify medium effects while maintaining practicality within resource constraints. Specifically, a sample of 50 allows for the application of parametric tests such as t-tests and correlation analyses, which assume reasonably normal distributions of the variables involved due to the Central Limit Theorem.

The size of the sample directly influences the reliability and generalizability of the findings. Larger samples tend to better approximate the population, reducing sampling error and increasing confidence in the results. With n = 50, my analysis will be guided by the recognition that the findings may be more representative than smaller samples but might still be limited in detecting very small effect sizes. Consequently, reporting will include confidence intervals and effect sizes to provide clearer insights into the magnitude of observed effects, in addition to p-values.

Selection and Justification of the Statistical Procedure

Considering the nature of my research question—which involves examining the relationship between two variables—Pearson’s correlation coefficient is the appropriate statistical procedure. My data consists of continuous variables: hours of sleep and test scores, collected from 50 participants. The research question aims to determine whether a relationship exists between sleep duration and academic performance.

The choice of correlation analysis is justified by the need to quantify the strength and direction of the association between these two variables. In alignment with the guidelines from the Choose Your Test document, a correlation test is appropriate when the research question explicitly seeks to identify the degree and nature of relationship between two continuous variables. It assumes linearity, normality, and homoscedasticity, which I plan to verify through preliminary data checks.

Alternatively, if the analysis had involved comparing means between two groups—such as students who exercised versus those who did not—an independent samples t-test would be suitable. But since the focus here is on the association between two continuous variables, correlation is most appropriate.

Conclusion

In sum, my chosen sample size of 50 participants provides a reasonable foundation for the analysis, balancing practicality and statistical robustness. This size informs the sensitivity to detect medium effects and guides the interpretation and reporting of the results with a focus on effect sizes and confidence intervals. The selected statistical procedure—correlation analysis—is justified by the research question's aim to explore the relationship between sleep and academic performance, aligning with guidelines from the Choose Your Test document. This method will effectively illuminate whether and how these variables are related, supporting the overall research objectives.

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