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NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP

NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP

Grand Canyon University NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP-Step-By-Step Guide

 

This guide will demonstrate how to complete the Grand Canyon University NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP  assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.

 

How to Research and Prepare for NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP                  

 

Whether one passes or fails an academic assignment such as the Grand Canyon University NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP  depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.

 

After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.

 

How to Write the Introduction for NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP                  

The introduction for the Grand Canyon University NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.

 

How to Write the Body for NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP                  

 

After the introduction, move into the main part of the NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP  assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.

 

Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.

 

How to Write the Conclusion for NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP                  

 

After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.

 

How to Format the References List for NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP                  

 

The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.

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NUR 705 Assignment 12.1: Parametric and Non-parametric Tests in JASP

Introduction

This week, you will run some descriptive statistics on a data set in JASP to evaluate skewness and kurtosis.

Assignment Guidelines

  1. Download the NUR705 Week 12 Dataset (CSV) (Links to an external site.).
  2. Using JASP, run descriptive statistics on the variable: “Beginning Weight in pounds (ratio)”
  3. Under plots, check basic plots; distribution plots.
  4. Under statistics, run mean, std. deviation, minimum, maximum, skewness, and kurtosis.
  5. Review pages 146–148 in your Kim, Mallory, & Vallerio textbook under “Step 3: Check Assumptions of the Chosen Test.”
  6. Answer the following questions on how this variable meets or does not meet statistical assumptions: Evaluate skewness and kurtosis of “Beginning Weight in pounds.” Does this meet or not meet normal distribution? Have any statistical assumptions been violated? Explain your answer.
  7. Run this again using the variable “Ending Weight in pounds.”
  8. Answer the following questions on how this next variable meets or does not meet statistical assumptions: Evaluate skewness and kurtosis of “Ending Weight in pounds (ratio). Does this meet or not meet normal distribution? Have any statistical assumptions been violated? Explain your answer.
  9. Address the following questions for both variables: What level of measurement do you need to meet assumptions for a variable to be considered normally distributed? What does independence of the data mean? Did both variables meet this assumption and how?
  10. Copy a screenshot of your data for both variables into a Word document and answer the questions in the same document.
  11. Submit your assignment to the tab in Canvas.

Submission

Submit your assignment and review full grading criteria on the Assignment 12.1: Parametric and Nonparametric Tests in JASP page.

Parametric and Nonparametric Tests Transcript

Today’s topic is about parametric and non-parametric tests, and let’s get started. Why are you interested in this topic? You want to calculate a hypothesis test but you don’t know exactly what the difference is between a parametric and a non-parametric test, and you’re wondering when to use which test. If you want to calculate a hypothesis test, you must first check the assumptions. One of the most common assumptions is that the data used must show a certain distribution, usually the normal distribution. Simplified, we could say that if your data is normally distributed, parametric tests are used. For example, the t-Test, the ANOVA, or a Pearson correlation. If your data is not normally distributed, you use a non-parametric test. For example, Mann-Whitney U test or Spearman correlation.

What about the other assumptions? Of course, you still have to check if there are further assumptions for the respective test, but in general, there are less assumptions for non-parametric tests than for parametric tests. So, why then do we need parametric tests? Parametric tests are generally more powerful than non-parametric tests. What does that mean? Let’s say you have formulated your null hypothesis, which is, for example, the salary of men and women does not differ. Whether the null hypothesis is rejected depends on the following things, on the difference in the salary and also on the sample size. In a parametric test, a smaller difference in the salary or a smaller sample is usually sufficient to reject the null hypothesis. If possible, always use parametric tests.

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Now there’s still two open topics. First, I’ll show you what the most common parametric and non-parametric tests are, and then I will explain to you how you can easily calculate these tests online with DATAtab. Usually for the most common parametric tests, there is always a non-parametric counterpart. If you only have one sample, the parametric test is the simple t-test and the non-parametric test is the Wilcoxin test for one sample. If you have two dependent samples, on one side it is the paired t-Test and on the other side it is the Wilcoxin test. If we look at independent samples, it’s the unpaired t-Test and the Mann-Whitney U test. If you don’t know exactly what dependent and independent samples are, just watch my [inaudible 00:03:24] about it. You can find the link in the video description below. If you have more than two independent samples, you use the analysis of variants or the Kruskal-Wallace test.

Finally, if you have more than two dependent groups, you use the ANOVA with repeated measures or the Friedman Test. If you want to calculate the correlation between two variables, you can use either the Pearson correlation or the Spearman correlation. You can find the link to this overview in the video description.

If you want to analyze your data by using DATAtab, you just visit datatab.net and you click on the statistics calculator. Then you can copy your data into this table and click on this tab, which says t-Test, Chi square-test, ANOVA, and so on. Let’s say that you want a test if there is a difference between men and women in the salary. You choose salary as metric variable and as a nominal variable gender. Then automatically a t-Test for independent samples is calculated, which is a parametric test. If you want, you can also click here, then a non-parametric test will be calculated. Then you can see that the Mann-Whitney U-Test is calculated, which is the non-parametric counterpart to the t-Test for independent samples. I hope you like this video and thank you for watching.

Normal Distributions

Review the video on Normal Distributions:

Normal Distributions Transcript (Links to an external site.)


Parametric vs. Nonparametric Tests

Review the video on Parametric vs. Nonparametric Tests:

Parametric vs. Nonparametric Tests Transcript (Links to an external site.)


Parametric and Nonparametric Tests

Review the video on Parametric and Nonparametric Tests:

Parametric and Nonparametric Tests Transcript

Lesson 1: Distributions of Data—Parametric vs. Nonparametric

Introduction

Up until this point, you have examined statistical tests that are conducted when the distribution of data follows a normal distribution. However, not all data that is collected in quantitative studies will end up normally distributed. This is especially true in studies when sample sizes are not as large as they need to be to reach statistical power or if participants are not randomized.

Even though collected data may not meet the assumptions of a proposed statistical test, it is not a lost cause. If this is the case, a researcher can conduct a nonparametric counterpart test for analysis of data.


Learning Outcomes

At the end of this lesson, you will be able to:

  • Describe how to identify data that is not-normally distributed.
  • Define skewness and kurtosis.
  • Evaluate assumptions of nonparametric tests of differences.
  • Distinguish between parametric tests and nonparametric tests.

Before attempting to complete your learning activities for this week, review the following learning materials:


Learning Materials

Read the following in your Polit & Beck (2021) Nursing research; Generating and assessing evidence for nursing practice textbook:

  • Chapter 18, p. 392, section Parametric and Nonparametric Tests
  • Chapter 18, p. 396, section Nonparametric Two-Group Tests
  • Chapter 18, p. 400, section Nonparametric “Analysis of Variance”

Read the following in your Kim, Mallory, & Vallerio (2022) Statistics for evidence-based practice in nursing textbook:

  • Chapter 6, pp. 111–112 (focus attention on definitions of skewness and kurtosis)
  • Chapter 13, “Nonparametric Tests”
Assignment 12.1: Parametric and Nonparametric Tests in JASP Rubric
Criteria Ratings Pts
Screenshots
3 to >2 pts
Meets Expectations

Completed and correct screenshots of the results from JASP are included.

2 to >0 pts
Does Not Meet Expectations

Completed screenshots are not included.

/ 3 pts
Narrative
4 to >3 pts
Meets Expectations

Narrative includes an adequate interpretation of your results, including how the variable meets or does not meet statistical assumptions and the level of measurement needed to meet assumptions for a variable to be considered normally distributed.

3 to >1 pts
Nearly Meets Expectations

Narrative includes an interpretation of your results, including how the variable meets or does not meet statistical assumptions and the level of measurement needed to meet assumptions for a variable to be considered normally distributed.

1 to >0 pts
Does Not Meet Expectations

Narrative does not include an interpretation of your results, including how the variable meets or does not meet statistical assumptions and the level of measurement needed to meet assumptions for a variable to be considered normally distributed.

/ 4 pts
Documentation and Mechanics
4 to >3 pts
Meets Expectations

No errors in grammar, spelling, punctuation, or sentence structure.

3 to >1 pts
Nearly Meets Expectations

Few errors in grammar, spelling, punctuation, or sentence structure.

1 to >0 pts
Does Not Meet Expectations

Numerous and distracting errors in grammar, spelling, punctuation, or sentence structure.

/ 4 pts
APA Formatting
4 to >3 pts
Meets Expectations

APA formatting is followed in accordance with the 7th edition for reporting statistical results.

3 to >1 pts
Nearly Meets Expectations

Contains one to two APA errors in reporting statistical results.

1 to >0 pts
Does Not Meet Expectations

Does not follow APA 7th edition guidelines.

/ 4 pts
Total Points: 0