Pharmacy AI · Module 4 · Unit 2 · Practical 1

Research Data Analysis Bench

Aim — To take a real trial dataset from raw to reportable — inspecting it for problems, cleaning it defensibly, choosing and running the correct statistical test, interpreting the output honestly, and catching the errors in an AI-generated analysis.

Your dataset

A colleague has run a small randomised trial of a pharmacist-led adherence intervention and has sent you the dataset to analyse before submission. The file has 25 rows and it is not clean.

  1. Inspect before you analyse. Click any row you believe has a problem — there are four.
  2. Every cleaning decision must be defensible and documented. Deleting inconvenient data is misconduct, not cleaning.
  3. The test follows from the data type and design, not from which test you happen to know.
  4. Finally, an AI tool has drafted the results paragraph. Three of its five statements are wrong.

Assessment rubric

Assessment criteriaMarks
Data inspection — problems identified20
Handling missing data15
Handling the outlier15
Choice of statistical test20
Interpretation of the result15
Verification of the AI-generated analysis15
Total100

Pass 50. Analytical Integrity is reported separately.

Achievement badges

🔬 Careful Inspector🧹 Defensible Cleaning 📊 Right Test🎯 Honest Interpretation🏅 AI-Proof Analyst

Open the dataset

Alizon Teaching Hospital · pharmacist-led adherence trial · dataset ADH-24

Analysis report

Complete the analysis to generate your report, then write and submit it below.