This post covers Heart Failure Clinical Data, as detailed below.
The purpose of this formative assessment is to help you conduct and interpret a chi-square statistical analysis using a real healthcare dataset. You will develop a research question, test a null hypothesis, and evaluate both the statistical and clinical significance of your findings. These skills are essential for interpreting research results and for planning and evaluating healthcare change projects.
Required Tools and Dataset
Statistical Software
· jamovi (free statistical software) Download jamovi from the official websiteLinks to an external site.
Guided Resources
· Stats Made Easy: jamovi Step-by-Step Guides Access the jamovi step-by-step guidesLinks to an external site.
· jamovi YouTube Channel Watch instructional videos on the jamovi YouTube channelLinks to an external site.
Dataset
· Heart Failure Clinical Data (Kaggle dataset) Access the Heart Failure Clinical Data dataset on KaggleLinks to an external site.
Instructions
Step 1: Dataset Review and Variable Selection
· Review the description of the variables in the Heart Failure Clinical Data dataset.
· Select two categorical variables with levels of measurement appropriate for a chi-square analysis.
Step 2: Title Page
· Use APA format.
· The title of your paper should clearly reflect the two variables being tested.
Step 3: Dataset Description (Methods Equivalent)
In the first paragraph of the paper:
· Do not label this section as “Introduction.”
· The title of the paper should be repeated at the top of the page.
Describe:
· The source of the dataset
· The general purpose of the dataset
· The number of subjects
· The number of variables
· The general types of variables included
Cite the dataset. For this assignment, this section serves as the equivalent of a sampling plan in a published research study and represents how you are “collecting data.”
Step 4: Research Question and Hypotheses
1. Write a research question that includes:
· A population
· Two variables appropriate for chi-square analysis
2. Identify:
· The independent variable (IV)
· The dependent variable (DV)
3. Write:
· A null hypothesis
· An alternative hypothesis
Your hypotheses should include the population, IV, DV, the descriptive statistic being tested, and the relationship being examined.
Step 5: Rationale for Chi-Square
Describe:
· Why the chi-square test is appropriate for your research question
· The assumptions of the chi-square test
· How the level of measurement and number of groups support its use
Step 6: Descriptive Statistics
Use a Level 1 heading: Results
1. Using jamovi, calculate the appropriate descriptive statistics for each variable.
2. Copy and paste the table of descriptive statistics into your paper.
3. Generate a graph that appropriately illustrates the descriptive statistics for both variables.
· If the y-axis does not extend from the lowest possible value to the highest possible value, describe what the correct range should be.
· Explain why the selected y-axis range is important for accurately illustrating the data.
4. Interpret the descriptive statistics:
· Describe trends or differences in frequencies or percentages.
· Discuss whether the observed differences appear clinically meaningful.
· Consider feasibility, cost, time, and patient impact when evaluating clinical relevance.
Step 7: Inferential Statistics
1. Continue the Results section by copying and pasting the chi-square inferential results table from jamovi.
2. Report the:
· Chi-square statistic
· p-value
· Alpha level (0.05)
3. Based on the chi-square results, determine the decision regarding the null hypothesis:
· If p 0.05, fail to reject the null hypothesis.
4. Interpret what this decision means in relation to your research question.
5. Report and interpret:
· Effect size
· Confidence interval (CI)
· Odds ratio (OR)
Explain how these values contribute to understanding the clinical significance of the results and whether the clinical significance aligns with the statistical significance.
Step 8: References
Include a reference list that contains:
· Sources supporting healthcare practice and policy decisions (published within the last 5 years)
· Sources supporting statistical concepts (published within the last 10 years)
Submission Format
· Word Document
Rubric
Formative Rubric (4)
Formative Rubric (4)
Criteria
Ratings
This criterion is linked to a Learning OutcomeScholarly Writing
AffirmedWriting is formal in language, avoiding colloquialisms, slang, and overly informal expressions.
Not AffirmedWriting includes colloquialisms, slang, and overly informal expressions.
This criterion is linked to a Learning OutcomeWriting Mechanics
AffirmedMinor spelling, grammar, and/or punctuation errors present, and/or sentence structure lacks minor elements of professional writing, and/or paragraphs are consistently developed. (1-2 errors)
Not AffirmedMultiple spelling grammar and/or punctuation errors present and/or sentence structure does not meet professional writing standards, and/or paragraphs are minimally developed. (more than 2 errors)
This criterion is linked to a Learning OutcomeClarity of Content
AffirmedWriting demonstrates a strong connection between ideas, ensuring that the reader can follow the logical progression of the arguments.
Not AffirmedWriting lacks a connection between ideas, and there is no logical progression of the arguments.
This criterion is linked to a Learning OutcomeAll Aspects Addressed
AffirmedWriting addresses multiple relevant aspects of the topic with sufficient detail and analysis, providing a thorough understanding.
Not AffirmedWriting fails to address relevant aspects of the topic with insufficient detail or analysis.
This criterion is linked to a Learning OutcomeAPA Sources (when appropriate)
AffirmedCitations and references follow the APA style guide, with fewer than 2 errors.
Not AffirmedCitations and references are not included when appropriate or do not follow the appropriate APA style guide. There are more than 2 errors.
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