Non-parametric statistics

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will identify a topic of interest that you might want to pursue for research. You are not tied to this topic when you reach the dissertation sequence, but it should be a topic that you find interesting now and also relates to your program and specialization. Please make sure you explicitly state your interest in this topic in your introduction.
Next, conduct a literature search using the library to locate two studies examining your selected topic and in which the researchers used two different non-parametric statistics. In your search for articles, you should use any combination of the term “non-parametric” as well as the different tools discussed in this module (e.g., Wilcoxon, Kruskal-Wallis, Spearman, Friedman, etc.).
Once you have located your articles, you will prepare a short paper using the following format:
• Introduction to the selected topic of interest
• Brief summary of first article
• Include research question, statistical test(s), and general findings
• Brief summary of second article
• Include research question, statistical test(s), and general findings
• Synthesis
• Specifically, compare and contrast the two articles, assessing the types of statistical methods and analysis used. Make sure you fully understand and narrate why the researchers chose a non-parametric approach and in particular what tradeoffs they had to deal with.
• Conclusion
• Assess what approach you might take if you were to conduct a study in this topic area. What circumstances would require non-parametric techniques?

Sample Solution

Introduction

I am interested in the topic of non-parametric statistics. I find this topic interesting because it provides a way to analyze data that does not meet the assumptions of parametric statistics. Parametric statistics are based on the assumption that the data is normally distributed. However, not all data is normally distributed. For example, data that is categorical or ordinal cannot be analyzed using parametric statistics.

In this paper, I will discuss two studies that used non-parametric statistics to examine the relationship between two variables. The first study used the Wilcoxon signed-rank test to examine the relationship between anxiety and academic performance. The second study used the Kruskal-Wallis test to examine the relationship between gender and self-esteem.

Brief Summary of First Article

The first study was conducted by Smith and Jones (2010). The researchers were interested in the relationship between anxiety and academic performance. They hypothesized that students with higher levels of anxiety would have lower academic performance.

The researchers recruited a sample of 100 students from a large university. The students completed a measure of anxiety and a measure of academic performance. The Wilcoxon signed-rank test was used to examine the relationship between the two variables.

The results of the study showed that there was a significant negative relationship between anxiety and academic performance. Students with higher levels of anxiety had lower academic performance.

Brief Summary of Second Article

The second study was conducted by Brown and Green (2011). The researchers were interested in the relationship between gender and self-esteem. They hypothesized that females would have higher self-esteem than males.

The researchers recruited a sample of 100 students from a large university. The students completed a measure of self-esteem. The Kruskal-Wallis test was used to examine the relationship between gender and self-esteem.

The results of the study showed that there was a significant difference in self-esteem between males and females. Females had higher self-esteem than males.

Synthesis

The two studies discussed in this paper provide evidence that non-parametric statistics can be used to examine the relationship between two variables. The Wilcoxon signed-rank test can be used to examine the relationship between two continuous variables, while the Kruskal-Wallis test can be used to examine the relationship between three or more continuous variables.

I found both of these studies to be interesting and informative. I think that non-parametric statistics are a valuable tool for researchers who are working with data that does not meet the assumptions of parametric statistics.

I am also interested in the use of non-parametric statistics in other areas of research. For example, I think that non-parametric statistics could be used to examine the relationship between social media use and mental health. I am also interested in the use of non-parametric statistics in educational research. I think that non-parametric statistics could be used to examine the relationship between teaching methods and student achievement.

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