Identifying Variables in a Research Article
Identifying Variables in a Research Article
As a doctoral candidate who is preparing for the capstone project, you will be expected to carefully read and understand the methods sections of research articles. In this course we will slowly work our way through each of the parts of this section that are related to data analysis. In this unit, we will focus our attention on research study variables that make up a data set.
Often the authors of published peer-reviewed articles will not explicitly describe the statistical categories of the variables they are studying, but by the end of this unit, you should be able to deduce the role of the study variables by reading how they are described in context. In this discussion, you will have an opportunity to use this unit’s resources, along with your detective skills, to determine whether a variable is dependent or independent.
Instructions
For this discussion, readone of the peer-reviewed articles linked in Resources. Using this unit’s readings, media, and other resourcesas guidance, complete the following:
Identify and describe the dependent and independent variables in the study.
For the dependent variables, identify the level of measure (categorical, ordinal, interval, ratio) and justify your answer.
Locate and report on any Internet sources that you found to help you in understanding this exercise. Be sure to include each URL in your post.
Remember to refer to the guidelines in the Faculty Expectations message (FEM) as you prepare your post.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM. How do their reported variables compare to yours?
Learning Components
This activity will help you achieve the following learning components:
Identify the variables in a study or article.
Review basic math and statistics terminology including variables, and dependent versus independent variables.
Write about statistical concepts clearly, accurately, and professionally.
Cite sources appropriately, using APA formatting.
Resources
Discussion Participation Scoring Guide.
Quality Improvement Methodologies Increase Autologous Blood Product Administration.
Fall Prevention in a Swiss Acute Care Hospital Setting.
A Pilot Feasibility and Acceptability Study of Yoga/Meditation.
NHS8070 Evaluation and Interpretation of Data in Health Care
Unit 2 Discussion
DQ1 SPSS Practice: Setting Up a Data Set
Context
To best prepare for the upcoming assignments, you should thoroughly familiarize yourself with the basic operations of SPSS. In addition to the unit’s SPSS-based reading, media, and resources, we strongly encourage you to explore the Internet for complementary explanations. Like learning a foreign language, the trick to retaining a new concept, word, or practical skill is to see how it is used in various contexts. The same is true for the terminology you will encounter in this course. If you look beyond this course to see how others use new SPSS terms, concepts, and functions, it will help you retain the information.
Instructions
For this discussion, you will be practicing data entry. We made the task a bit easier by linking a basic data set in Resources, the Emotional Well-Being (SF-36) Study. Refer to the additional helpful links in Resources as you prepare your post, and remember to follow the guidelines in the Faculty Expectations message (FEM).
Your objective is to simply perform data import from an Excel data file to SPSS (as this is often how you will obtain data from non-researchers). First, upload the Emotional Well-Being data setlinked in Resources (note this is an Excel file, so you will need to convert it for use in SPSS). Hint: Select the appropriate scale for each variable.
Identifying data levels.Data sets may have many different levels of data. The skill you will practice is learning to quickly look through labels in a data view and know immediately what type of data level you are looking at.
Run frequencies in SPSS. Frequencies are run on all levels of variables. Running frequencies helps youto identify problems with missing or out of range values for your variables. Frequencies will provide you with tables and pie charts to help you analyze the data.
Run the Explore module.The Explore module is run on the scale (interval or ratio) level data and the ordinal level data. It presents all the information you need to make decisions about ordinal and above level data (for example, 95% CI of the mean). Because of the way Explore works, it is less helpful with nominal data.
Be sure to save a copy of this newly created SPSS data set titled Emotional_Well-Being_(your initials) to the file folder you created for your SPSS work. You willuse this data set againin later units.
Complete the following for your initial post:
What did you use for your variables (nominal, ordinal, interval, ratio)?
What were the measures of central tendency?Standard deviation?Minimum?Maximum?
Describe one or two of the challenges you found while performing these exercises and how you resolved the issues. Where appropriate, provide the address of any website that helped you.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
Address one or more of the following:
How do thereported challenges and resolutions of your peers compare to yours?
Do you have any suggestions that could help your peers?
Resources
Discussion Participation Scoring Guide.
Emotional Well-Being (SF-36) Study Data Set [XLSX].
DQ2 SPSS Practice: Create a Pivot Table, Bar Graph, and Histogram
Context
It is considered a best practice for researchers to spend some time, immediately after data entry, to review the data.
Is the data complete, or are there missing pieces that must be investigated? Are the data ranges what one might reasonably expect?
Are there extremes in reported values that suggest an unusual population or possible errors that will need to be traced back to the document of origin?
In the early stages, it is important for a researcher to get a bird’s-eye view of their data before diving into deeper, more complex analyses. Eventually the data will need to be cleaned, but for now the researcher just needs to identify some basic information.To this end, SPSS provides some nice tools—the most basic being the pivot tables and histograms—to easily summarize and visualize interval/ratio data, no matter how large or small. Categorical data can also be summarized with a pivot table, but you will need to use a bar graph instead of a histogram. Do you know the difference?
Instructions
For this practice exercise, you will need to upload the data set (Emotional Well-Being_your initials) you created.
Using this data set and the video instructions linked in Resources, create two or three pivot tables of your choice.
Create a bar graph for the variable Gender, and then a histogram for the variables Age and Baseline SF-36 Well-Being Scores.
In your post for this discussion:
Post your creations (pivot table, bar graph and histogram) in the discussion area.
Explain the difference between a bar chart or graph and a histogram.
Summarize, in your own words, the most important messages you find in each of the outputs you created.
Describe one or two of the challenges you found while performing these exercises and how you resolved the issues. Where appropriate, provide the address of any website that helped you.
Remember to refer to the guidelines in the Faculty Expectations message (FEM) as you prepare your post.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
Address one of more of the following in your response:
How do the challenges and resolutions of your peers compare to yours?
How did your conclusions relatedto the most important messages you found in each of the outputs you created compare to those of your peers?
Learning Components
This activity will help you achieve the following learning components:
Set up a dataset using a survey.
Create a demographic table from given data.
Interpret the information presented in a demographic table.
Write about statistical concepts clearly, accurately, and professionally.
Resources
Discussion Participation Scoring Guide.
Emotional Well-Being (SF-36) Study Data Set [XLSX].
World Health Organization Data – Using a Pivot Table to Make Sense of It [Video] | Transcript.
Finding and Using Data in Global Health [Video] | Transcript.
Pivot Tables in SPSS. [Video] | Transcript.
NHS8070 Evaluation and Interpretation of Data in Health Care
Unit 3 Discussion
SPSS Practice: Performing a Descriptive and Diagnostic Preliminary Examination of the Data
In preparation for this week’s practice, you will need to know how to use SPSS to perform a basic descriptive statistical analysis, find any abnormal data points (outliers), and perform a normality test of data. Refer to the links in Resources to help you complete this post, and remember to follow the guidelines in the FEM.
Instructions
For this discussion, use the Emotional Well-Being (SF-36) data set you previously created (and were directed to save):
Perform and report the descriptive statistics for the following variables: Age, Gender, and Baseline Well-Being Score (hint: you need to know what type of data is found for each variable before you choose the descriptive statistics you will show).
Run the following analysis:
In the Menu bar, clickAnalyze.
Find Descriptives.
Under Descriptives, add:
Age, Gender, and Baseline Well-Being Score to variables.
SelectOptionsand check those of interest.
CheckSave standardized valuesas variables.
Click OK.
Using the box-and-whiskers approach, create a graphic for each of the aforementioned variables (if appropriate) and identify any outliers.
Using the histogram tool, submit your creation in the discussion area (hint: histograms are only appropriate for certain types of variables) and state whether you think the data is normally distributed.
Describe one or two of the challenges you found while performing these exercises and how you resolved the issues. Where appropriate, provide the address of any website that helped you.
Refer to the helpful links in Resources as you prepare your post.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
Address one of more of the following in your response:
How do the challenges and resolutions of your peers compare to yours?
How did your graphics and conclusions drawn compare to your peers?
Learning Components
This activity will help you achieve the following learning components:
Identify the variables in a study or article.
Create a demographic table from given data.
Set up a dataset using a survey.
Interpret the information presented in a demographic table.
Write about statistical concepts clearly, accurately, and professionally.
Resources
Discussion Participation Scoring Guide.
Emotional Well-Being (SF-36) Study Data Set [XLSX].
3. Choosing Between Parametric & Non-Parametric Tests [Video].
Box Plot (Box and Whiskers): How to Read One and How to Make One in Excel, TI-83, SPSS.
NHS8070 Evaluation and Interpretation of Data in Health Care
Unit 4 Discussion
DQ1 Explaining the Impact of Sampling on Statistical Analysis
In preparation for this unit’s statistical analysis practice and the unit assignment, you will have an opportunity to explore some basic statistical concepts that involve the sample.
The Emotional Well-Being data set is based on a fictional study in which a researcher was interested in determining if a vegetarian diet was a beneficial to the well-being of people living in Alaska, as was found in other research locations where sun exposure was greater.
Based on previous publications, the researcher selected the Short Form Health Survey (SF-36) as the instrument for measuring the efficacy of the different dietary treatments. The current data set recruited a fairly large number of participants (n=72) to answer this question.
Instructions
For this post, refer to the guidelines in the FEM and use the provided data set linked in Resources to complete the following:
Create two smaller samples (n=10 and n=5) from the original Emotional Well-Being population data setusing SPSS’s Stratified Random Sampling tool.
Performadescriptiveanalysisofthekey variables in each of these new data sets(variables:BaselineSF-36Well-BeingScore, Post-Tx Well-Being Score,BMI, Age)and compare your resultsto the original,larger data set’s descriptive analysis results.Report your findings.
Use this unit’s resources to help youexplain your results in terms of differences in sampling error, sample representativeness, descriptive statistical estimates with related confidence interval, and power.
Speculate as to what would have happened were the sample size smaller.
Describe one or two of the challenges you found while performing these exercises and how you resolved the issues. Where appropriate, provide the address of any website that helped you.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
Address one of more of the following in your response:
How do the challenges and resolutions of your peers compare to yours?
How did your findings regarding sampling error, sample representativeness, confidence, etc., compare to your peers?
Learning Components
This activity will help you achieve the following learning components:
Prepare data for analysis.
Set up a dataset using a survey.
Identify the influence of sample size and influence of effect size.
Identify sampling methods and the difference between populations and samples.
Analyze the analytical testing approach in a quantitative study.
Write about statistical concepts clearly, accurately, and professionally.
Resources
Discussion Participation Scoring Guide.
Emotional Well-Being (SF-36) Study Data Set [XLSX].
NHS8070 Evaluation and Interpretation of Data in Health Care
Unit 5 Discussion
DQ1 SPSS Practice: Assumptions and Normality
Preparation
For this discussion select one of the data sets we have been using in class. During this discussion you will assess the normality of the data set you chose.
Instructions
For this discussion, start by answering the following questions, based on your readings and research:
What does the assumption of normality mean?
When does the assumption matter?
Next, using the data set of your choice from class, assess the normality of the data.
Include your data output tables in your post.
Write a brief descriptive analysis of the normality of the data as part of your post.
Finally, describe one or two of the challenges you found while performing these exercises and how you resolved the issues. Where appropriate, provide the address of any website that helped you.
Remember to refer to the guidelines in the FEM as you prepare your post.
If you have questions about how to choose an appropriate test to assess normality, you may wish to review How to Choose a Statistical Test, which is linked in the resources.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the Faculty Expectations message.
Address one of more of the following in your response:
How do the challenges and resolutions of your peers compare to yours?
How did your assessment of the normality of the data from the same data set compare to those of your peers?
Learning Components
This activity will help you achieve the following learning components:
Identify the Pearson Correlation and the Spearman Correlation.
Create a scatterplot for a combination of variables to identify the graphic nature of the relationship.
Interpret the information presented in a demographic table.
Identify the influence of sample size and influence of effect size.
Analyze the analytical testing approach in a quantitative study.
Write about statistical concepts clearly, accurately, and professionally.
Resources
Discussion Participation Scoring Guide.
How to Choose a Statistical Test [PPTX].
Emotional Well-Being (SF-36) Study Data Set [XLSX].
DQ2 Critiquing the Literature: Assumptions of Statistical Tests
Preparation
In preparation for this discussion, make sure you have read the article, “Are Assumptions of Well-Known Statistical Techniques Checked, and Why (Not)?”
Instructions
Hoekstra, Kiers, and Johnson (2012) state,”Our findings show that researchers are relatively unknowledgeable when it comes to when and how data should be checked for violations of assumptions of statistical tests.”
Complete the following for your initial post for this discussion, remembering to adhere to the guidelines in the FEM:
Describe to what extent you find this statement to be accurate, based on your experience, readings, and research.
Provide relevant examples and rationale for your explanation.
Review the researchquestion descriptionsin the Appendix of the article, and select one of them. For the one you selected:
List the assumptions for the statistical analysis that should be used for that question. Note:You do not need to perform the assumptions; you will get to do that in future units!
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
Address one of more of the following in your response:
Compare your response to the authors’ statement to that of your peers.
Compare your list of assumptions for the question to the list(s)of your peer(s) if you selected the same research question description from the Appendix.
Reference
Hoekstra, R., Kiers, H. A. L., & Johnson, A. (2012).Are assumptions of well-known statistical techniques checked, and why (not)?Frontiers in Psychology,3, 137-145.
Learning Components
This activity will help you achieve the following learning components:
Cite and summarize a selected article.
Analyze the analytical testing approach in a quantitative study.
Assess the overall methodological quality of a study or article.
Write about statistical concepts clearly, accurately, and professionally.
Cite sources appropriately, using APA formatting.
Resources
Discussion Participation Scoring Guide.
APA Module.
Capella University Library.
Are Assumptions of Well-Known Statistical Techniques Checked, and Why (Not)?.
NHS8070 Evaluation and Interpretation of Data in Health Care
Unit 6 Discussion
DQ1 SPSS Practice: Correlation Testing
To best prepare for the assignment in this unit, you must become familiar with some basic statistical skills related to correlation testing. Although there are several tests that you could choose from, such as Pearson, Spearman, Kendall, and Biserial, you will only need to understand the basic differences for two slightly different correlation tests: Pearson correlation and Spearman correlation.
Before performing any inferential statistical analysis, it is common for a researcher to look for relationships among the various variables for which data has been collected.
For example, in our scenario, we want to find out if a change to a vegetarian diet from a typical American omnivorous diet will have an effect on emotional well-being. Before we come to that part of the analysis, however, it is a good idea to see if there are other factors that might influence the study results. It is entirely possible that there may be some hidden influence on the outcome that is related to age or BMI. We will explore just one statistical detective method that can be used to address this issue.
Instructions
For this discussion, refer to the helpful links in Resources and use the Alaska study’s Emotional Well-Being Corrected data set to perform the following analyses for only three variables that have interval/ratio data: Age, BMI and Baseline SF-36 Scores:
Pearson Correlation
Assess the selected variables for outliers and normal distribution and report which type of statistical correlation testing would be the most appropriate.
Create a scatterplot for each selected combination of the above variables to identity the graphic nature of the relationship.
Perform a Pearson Correlation test on the following, regardless of whether the data distribution looks normal: relationship between Age and BMI, then relationship between BMI and Baseline SF-36 scores.
Report the results as the magnitude of the relationship (correlation coefficient) and direction of the relationship (positive or negative).
Spearman Correlation
Perform a Spearman Correlation test regardless of whether the data distribution looks normal for the same two-variable combinations.
Report the results.
Comparison
Explain the differences between the Pearson Correlation and the Spearman Correlation, including when to use each test, advantages, and disadvantages of each.
Describe one or two of the challenges you found while performing these exercises and how you resolved the issues. Where appropriate, provide the address of any website that helped you.
Remember to refer to the guidelines in the FEM as you prepare your post.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
Address one of more of the following in your response:
How do the challenges and resolutions of your peers compare to yours?
How did the comparison between the Pearson Correlation and the Spearman Correlation of your peers compare to yours?
Learning Components
This activity will help you achieve the following learning components:
Prepare data for analysis.
Identify the chi-square test of independence.
Perform a chi-square test of independence.
Interpret the overall clinical meaning and limitations of the relationship of two variables, based on a correlation analysis and literature regarding age and stress.
Write about statistical concepts clearly, accurately, and professionally.
Resources
Discussion Participation Scoring Guide.
Emotional Well-Being (SF-36) Study Data Set [XLSX].
Pearson’s Product-Moment Correlation Using SPSS Statistics.
Spearman’s Rank-Order Correlation Using SPSS Statistics.
Scatterplots and Line-Fitting [Video] | Transcript.
How to Choose a Statistical Test [PPTX].
Variables, Hypotheses, and Types of Errors.
DQ2 Critiquing Public Health Literature Reporting: Quantitative Data
In preparation for your doctoral capstone project, you will need to develop advanced health numeracy (statistical knowledge, SPSS) and critical thinking in literacy. This discussion isan opportunity to collaborate with your peers in a critical analysis of a public health study.
Although it may require rereading the article a few times, you will find almost all the critical pieces of information necessary to answer the questions. Only one question will require some digging further from outside resources.
Instructions
Read the yoga and meditation study articleby Argawal, Kumar, and Lewis linked in Resources. The Rothman article is also included for your reference.
Complete the following for your initial post for this discussion, remembering to adhere to the guidelines in the FEM:
Identify the study’s target population. Who is being studied?
Describe the specific problem that the study authors discovered in their research that prompted them to do this study.
Describe the intervention; cite at least one previous study used in this article to justify the intervention. Locate the article to find supporting efficacy data.
Describe all the instruments (assessment tools) that 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 Faculty Expectations message. How do their analyses compare to yours?
Learning Components
This activity will help you achieve the following learning components:
Cite and summarize a selected article.
Identify sampling methods and the difference between populations and samples.
Analyze the analytical testing approach in a quantitative study.
Write about statistical concepts clearly, accurately, and professionally.
Cite sources appropriately, using APA formatting.
Resources
Discussion Participation Scoring Guide.
APA Module.
Capella University Library.
A Pilot Feasibility and Acceptability Study of Yoga/Meditation.
Perspective: The Role of Numeracy in Health Care.
The Value of a Research Critique to Translate Evidence Into Practice.
NHS8070 Evaluation and Interpretation of Data in Health Care
Unit 7 Discussion
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.
NHS8070 Evaluation and Interpretation of Data in Health Care
Unit 8 Discussion
Statistical Practice: Student T-Test
To best prepare for the upcoming assignments, you must understand how to perform and interpret paired several different t-tests. SPSS makes it relatively easy to perform parametric testing.
To add to your statistical programming skills and prepare you for the next unit, we will be using SPSS to solve the parametric t-testing in this unit.
Instructions
For this discussion, use the data found in the Emotional Well-Being data set you created previously. You will have to use two t-tests: independent samples (unpaired) t-test and the dependent samples (paired) t-test.
Independent Samples (Unpaired) T-test
To determine the varying effects of the dietary treatment on males versus females (which are, admittedly, “independent”of each other), perform an independent samples t-test on the Well-Being dependent variable in male participants compared to the same scores in female participants. Note you will need to create a new dependent variable related to the treatment-related change in well-being scores (Hint: Change score = Post-Tx Well-Being – Baseline SF-36 Well-Being Score).
Dependent Samples (Paired) T-test
Next, to compare the effects of the Dietary Treatment on the well-being of males at baseline to well-being scores in the same males after treatment, perform a dependent (paired) samples t-test for the dependent variable Well-Being (Hint: use Baseline versus Post-Tx).
For your initial post, complete the following:
Describe, in your own words, 2 or 3 research project scenarios in which to use these t-tests.
Report,using the Emotional Well-Being data set, the results of the t-testing that you perform. Report the appropriate all the statistical outcomes, including the 95% confidence interval.
Provide a 1-2 sentence practical interpretation that includes a practical explanation of the different confidence intervals, based on the results.
Remember to follow the guidelines in the FEM as you prepare your post.
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 normal and non-normal data distribution.
Identify ordinal data.
Identify the differences among t-testing, Mann-Whitney, and Wilcoxon Rank Sum testing.
Perform the appropriate tests with data for each question.
Identify the statistical output (estimate, p-value, confidence interval, effect size) from each statistical test.
Select the most appropriate testing strategy for a set of data.
Appropriately interpret the statistical output (estimate, p-value, confidence interval, effect size) resulting from each statistical test.
Describe the practical significance of statistical test results.
Resources
Discussion Participation Scoring Guide.
Emotional Well-Being (SF-36) Study Data Set [XLSX].
NHS8070 Evaluation and Interpretation of Data in Health Care
Unit 9 Discussion
Statistical Practice: Mann-Whitney and Wilcoxon Signed Rank (Nonparametric) Tests
The nonparametric tests that are being performed in this unit (Mann-Whitney U, the nonparametric equivalent of the independent t-test and the Wilcoxon Test, the nonparametric equivalent of the dependent t-test) are most often used if the interval or ratio data is not normally distributed or if the data being analyzed is at the ordinal (ranked) measurement level.
Tobest prepare for the upcoming assignments, you must understand how to perform and interpret paired t-tests.
Instructions
For this discussion, we will use the data scenario we described in Unit 8 (the various group comparisons for well-being), but we will pretend that the normal distribution assumption that we tested was violated (this is, test results suggest that the data is not normally distributed). You will perform a nonparametric Mann-Whitney test and a Wilcoxon signed-rank on the appropriate data.
Complete the following:
Describe, in your own words, an example of the type of research project scenarios where you should use these nonparametric statistical tests.
Report, using the Emotional Well-Being data set you created previously, the results of the two nonparametric tests that you perform. Be sure to include all relevant statistical outcomes.
Provide a one- or two-sentence practical interpretation of the results.
Remember to refer to the guidelines in the FEM as you prepare your post.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
Address one of more of the following in your response:
How do the challenges and resolutions of your peers compare to yours?
How do your practical interpretations compare to those of your peers?
Resources
Discussion Participation Scoring Guide.
Emotional Well-Being (SF-36) Study Data Set [XLSX].
NHS8070 Evaluation and Interpretation of Data in Health Care
Unit 10 Discussion
DQ1 Analyzing Research Questions
As you progress towards the end of your doctoral program, you will be asked to critique research studies and questions to build your foundational understanding of research best practices. Additionally, by critiquing existing research, you will improve your ability to create your own research questions and design your own research studies. These skills will be critical as you work towards the end of program doctoral project.
Instructions
Use the Capella University Library or a database of your choice to locate a peer-reviewed quantitative research study that interests youfrom the last 3 years.
Once you have located and read the research study, complete the following analysis for your discussion post:
Identify the research questions from the study.
Describe the sample used in the study.
Identify whether the study was cross-sectional or longitudinal.
Identify the variables and associated types of data.
Explain thestatistical analyses performed.
Were these analyses appropriate to answer the research questions? Why or why not?
Can you think of any limitations to this study?
Remember to refer to the guidelines in the Faculty Expectations message (FEM) as you prepare your post.
Response Guidelines
Read and respond to the posts of your peers according to the guidelines in the FEM.
In your response to your peer(s), comment on their explanation of the statistical analyses and limitations of the study.
DQ2 Course Reflection
In this course, you have learned how to apply quantitative analysis strategies to a number of health care issues.
For this discussion, reflect upon all the analyses you learned in this course, and address the following in your discussion post:
With what aspects of quantitative analysis do you feel most comfortable?What aspects are you still unsure about?
How do you plan on using these concepts and tests in your work, research, or a leadership situation?
Response Guidelines
Responding to your peers is optional for this discussion.
Resources
Discussion Participation Scoring Guide.
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