FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assessment 3
Sydney School of Public Health Semester 1, 2026

FMHU5002 Introductory Biostatistics
Data Analysis and Reporting Assignment
Due Date and Time: Sunday 17th May at 11:59pm, Sydney time.
Assignment Category: Submitted Work
Assignment Sub-category: Assignment
Weighting: 30%

Plagiarism and Academic Dishonesty Policy

You must complete your assignment alone. Submitting assignments that have been jointly completed
is not acceptable. Copying someone else’s work, using generative AI, or quoting from text without
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by plagiarism detection software. Serious penalties apply for plagiarism, collusion, or contract
cheating. Information about the University’s policy on academic honesty can be found at the following
site:

https://www.sydney.edu.au/students/academic-integrity.html

Late Penalties and Special Consideration

Unless you have an approved simple extension, special consideration or an academic plan, 1.5 marks
(5% of 30) will be deducted from your assignment mark per day (or part thereof) until Monday, May
27th, 11:59 PM (Sydney Local Time). Assignments submitted past this date without approved special
consideration or an academic plan will not be accepted and will be given a zero (0) mark. For students
seeking simple extensions or special consideration, please use the following site:

https://www.sydney.edu.au/students/special-consideration.html


FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assessment 3
Sydney School of Public Health Semester 1, 2026
Submitting your Assessment

Submit your assessment as a single file in .docx or .pdf format by 11:59 PM Sydney Local Time on
Sunday 17th May 2026 via Canvas (Assessments overview > Assessment 3: Data analysis and
reporting assignment > Assignment Submission – Click Here > Select the file to upload and then click
“Submit Assignment”). Do not attach a jamovi.omv or a .csv file with your submission.

If you have any administrative questions, please post them on the Canvas Discussion Board.
Go to Discussions > Data Analysis and Reporting Assignment Discussion.
Alternatively contact fmhu5002@sydney.edu.au

If you have difficulties submitting the assignment around the due time, please email
fmhu5002@sydney.edu.au directly with your assignment attached to avoid late penalties. The
timestamp of your email will be used as evidence of the date and time of your assignment submission.
Please note responses to emails will only occur during business hours on standard working days.


Important Notes:
• The data for the assignment has been simulated for the purposes of an assessment exercise.
As such, the outcomes from these analyses have no practical or clinical meaning.
• This assignment paper (including cover page, instructions, and data dictionary) is six (6) pages
in length. Please ensure you have all pages.
• The variable names and coding of the variables (i.e., the data dictionary) for your dataset are
included at the end of this assignment on page 6.
• Name your submission file with your student number (SID), unit of study code, and “A4” (e.g.,
311275249_FMHU5002_A4.pdf). Ensure all pages are numbered, and that your student
number is included in the header or footer of the document.
• Assignments are marked anonymously, so please do NOT put your name anywhere on the
assignment or submission title.
• Unless otherwise specified, any jamovi output presented must be edited to comply with the
recommendations for presenting results as covered in the Lecture 1 Notes.

FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assessment 3
Sydney School of Public Health Semester 1, 2026
Assignment Questions
A cross-sectional study was conducted within a local health district to investigate how different
lifestyle factors influence health outcomes in middle-aged adults. The study sample consists of 541
males aged 45 – 55 years old.
You have been asked to help analyse the data collected from the study and interpret the results.
Your collaborators within the local health district have provided you with the dataset (in the file
“FMHU5002_A3_2026.csv”, the data dictionary for which is provided on the last page of this
assignment document). A colleague has already screened the data and all values in the dataset
should be considered correct (i.e., you do not need to screen the data for impossible, implausible,
extreme, or missing values).

Question 1 (7 marks)
Research question 1: To evaluate the difference in fasting blood sugar between diabetic and non-
diabetic among middle-aged males.
a. Perform an appropriate analysis to assess whether there is an association between diabetes
status and fasting blood sugar. In your response, clearly state the null hypothesis that is being
tested, and provide a brief conclusion including any relevant statistical values. Your response
should be no longer than 5 sentences.

b. For fasting blood sugar, a difference of 2.5 mmol/L is considered clinically significant. Based
on your analysis in Question 1a, what can you conclude about the practical importance of the
results?

Question 2 (8 marks)
Research question 2: To evaluate the association between diabetic status and smoking status.
a. Perform an appropriate analysis to assess whether there is an association between diabetic
status and smoking status. In your response, clearly state the null hypothesis that is being
tested, and provide a brief conclusion including any relevant statistical values. Your response
should be no longer than 5 sentences.

b. Suppose another health district wishes to perform a similar study to examine the association
between diabetic status and smoking status. Due to budgetary constraints, they expect to only
be able to recruit half the number of participants. Explain how this sample size would affect
the statistical power to detect the same difference in smoking prevalence between diabetics
and non-diabetics as was observed in Question 2a. Also explain how this would affect the
probability of a type I error and the probability of a type II error. Your response should be no
longer than 5 sentences.
Note: you do NOT need to perform any sample size or power calculations to answer this
question.

FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assessment 3
Sydney School of Public Health Semester 1, 2026
Question 3 (4 marks)
Research Question 3: To assess the impact of diet type on Cholesterol.

To help answer Research Question 3, a colleague has been analysing the data and provided you with
the following jamovi output.
Linear Regression
Model Fit Measures
Model R R²
1 0.3222 0.1038
Note. Models estimated using sample size of N=541

Omnibus ANOVA Test
Sum of Squares df Mean Square F p
Diet 103.8291 1 103.8291 62.4497 <.001
Residuals 896.1427 539 1.6626
Note. Type 3 sum of squares

Model Coefficients - Cholesterol
95% Confidence Interval
Predictor Estimate SE Lower Upper t p
Interceptᵃ 4.6676 0.0741 4.5220 4.8131 63.0111 <.001
Diet:
high fat diet – low fat diet 0.8826 0.1117 0.6632 1.1020 7.9025 <.001
ᵃ Represents reference level

a. Provide an interpretation of the analysis based on the output above. In your response, clearly
state the null hypothesis that is being tested, and provide a brief conclusion including any
relevant statistical values. Your response should be no longer than 5 sentences.


FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assessment 3
Sydney School of Public Health Semester 1, 2026
Question 4 (11 marks)
Research Question 4: To assess the impact of diet type on Cholesterol controlling for physical activity
and BMI.

Based on input from clinical collaborators, your colleague informs you that physical activity and BMI
status should be considered as potential confounders of the relationship between Cholesterol and
diet.

a. Perform a multivariable regression analysis which examines the association between
Cholesterol and diet controlling for physical activity and BMI. Include the jamovi output from
the resulting model. Note: you do NOT need to re-format the jamovi output for this question.

b. Provide an interpretation of the analysis presented in Question 4a. In your response, clearly
state the null hypothesis that is being tested, and provide a brief conclusion including any
relevant statistical values. Contrast these results to those presented in Question 3a. Your
response should be no longer than 7 sentences.

c. Based on your model, estimate the predicted cholesterol level for a male from this population
with BMI = 24 and 1 hour of physical activity per week who is on a high fat diet. Repeat the
prediction for the same individual on a low fat diet.
Total = 30 marks



This is the end of the assignment questions.
The data dictionary for the assessment data set is provided below.


FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assessment 3
Sydney School of Public Health Semester 1, 2026
Data dictionary
Variable name Description Measure type
ID Identification number Nominal
Age Age, in years Continuous
Smoke Smoking status
0 = Not a current smoker
1 = Current smoker
Nominal
Activity Physical activity, measured as hours per week of
moderate to vigorous activity (h/w)
Continuous
SBP Systolic blood pressure, measured in mmHg Continuous
BMI Body mass index, measured in kg/m2 Continuous
Diet Diet type
1 = low fat diet
2 = high fat diet
Nominal
Diabetes_status Status
0 = Non-diabetic
1 = Diabetic
Nominal
Fasting_blood_sugar Fasting blood sugar, measured in mmol/L Continuous
Cholesterol Total cholesterol, measured in mmol/L Continuous


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