Grading Format and Weighting:
This assignment will be graded out of 10 and contributes to your continuous assessment mark.
Due Date:
15th November 2025 by 23:59
Late Submission Policy:
No late submissions will be accepted unless accompanied by valid documentation.
Course Learning Outcomes:
Upon completion of this assignment, students will be able to:
Apply non-parametric statistical methods using STATA.
Conduct and interpret Chi-square tests for independence.
Prepare and present results in the format of a scientific journal article.
Translate continuous variables into categorical variables for non-parametric analysis.
Integrate and update prior analytical work coherently.
Type of Submission:
Individual assignment submitted as part of a cumulative journal article.
Format:
Journal article style (continuous from previous assignments)
Length:
Approx. 2,000–2,500 words (excluding tables, figures, and references).
Reference Style:
Use APA (7th Edition) for all citations and references.
Naming Conventions:
Save the file as:StudentID_Assignment5_ChiSquare.docx
(e.g., 20250065_Assignment5_ChiSquare.docx)
How to Submit:
Upload the completed document to the class Moodle portal as directed. Notify your lecturer or class representative if you have any problems.
Context:
This assignment extends your learning from Assignments 2–4, moving from parametric tests to non-parametric statistics. It introduces the Chi-square test for independence, which is vital for analyzing relationships between categorical variables. This analysis is particularly useful when working with survey data, health outcomes, and other categorical measures.
By the end of the assignment, you will gain hands-on experience in preparing categorical datasets, performing chi-square analysis in STATA, and interpreting relationships between variables relevant to your field of study.
Description:
Students will use STATA to test the association between two categorical variables using the Chi-square test for independence. They will build on their existing dataset and journal article, converting their chosen dependent variable into a categorical form. Results must be integrated into the ongoing journal article, addressing all previous feedback.
Task:
Review your previous journal article (Assignments 2–4) and correct any issues noted in feedback.
Using your chosen dependent variable from the Google Sheet (link here):
Convert your dependent variable from a continuous/numerical measure into a categorical variable (e.g., BMI → “Underweight,” “Normal,” “Overweight”).
Select one categorical independent variable (e.g., Gender, Year of Study, Living Arrangement).
Using STATA, perform a Chi-square test for independence between the two categorical variables.
Clearly report your:
Hypothesis (Null and Alternative)
STATA output (including observed and expected frequencies)
Chi-square statistic, degrees of freedom, and p-value
Interpretation of results (indicating whether a significant relationship exists)
Add this analysis to your journal article, under the Results and Discussion sections.
Include relevant tables, graphs, and references.
Ensure that your final document integrates results from Assignments 2, 3, 4, and 5 coherently.
Required Tools:
STATA (Version 16 or higher) – for statistical analysis
Microsoft Word – for article preparation
Google Sheets – to confirm your dependent variable
Moodle – for file submission
Associated Course Materials:
Lecture slides on Non-parametric tests and Chi-square analysis
Practical STATA guide for Chi-square tests
Dataset and coding instructions from previous assignments
Example journal articles applying Chi-square tests in your area of study.
Rubric:
| Assessment Criteria | Description | Weight (%) |
|---|---|---|
| Data preparation and correct variable conversion | Appropriate recoding of numerical data into categories | 15% |
| Execution of Chi-square analysis in STATA | Correct application of the Chi-square test and output interpretation | 25% |
| Interpretation of results | Clear explanation of findings and implications for nutrition/health | 25% |
| Integration with prior assignments | Smooth continuation from earlier journal submissions and incorporation of feedback | 15% |
| Journal article presentation | Logical structure, clarity, and adherence to academic conventions | 10% |
| Proper referencing and formatting | Accurate use of APA referencing and presentation | 10% |
Examples:
A sample Chi-square analysis output and interpretation will be demonstrated during practical sessions.
Academic Integrity:
Each student must perform and submit their own work. Sharing results, copying code, or using others’ interpretations will be treated as academic misconduct.
Avoiding Plagiarism:
For best practices in citation and originality, consult:
👉 Preventing Plagiarism – Plagiarism.org
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