MAST20034 · Critical Thinking With Data
The Complete Exam Bible · S1 2026Critical Thinking with Data
Critical Thinking with Data is the University of Melbourne's second-year statistical-literacy subject — and its single most surprising feature is that there is nothing to compute. You are handed a graph, a study or a piece of statistical output and asked to name what is good, name what is wrong, and say how to fix it. The final exam is 60% of your grade, short-answer reasoning only — no calculator, no calculations, no software — sat with up to four sides of your own notes. As the marking criteria put it, “explaining your reasoning and choices is typically more important than any answer”: every mark is a because. This guide drills exactly that one move — name the concept → define it in a line → apply it to the scenario → state the consequence or fix — across the whole 11-week critique toolkit, from the PPDAC cycle to confounding to Bradford Hill.
What MAST20034 covers
Eleven reasoning weeks → one critique toolkit. Each links to its free chapter guide.
How MAST20034 is assessed
| Component | Weight | Format |
|---|---|---|
| Final exam | 60% | In-person, 3 hours, short-answer reasoning · no calculator, no calculations · bring-in: up to four sides (two A4 pages, double-sided) of your own notes · formal exam period |
| 4 short assignments | 20% | Individual · each a tight 200-word critique (APA 7) with hard word penalties — pick from the whole-class case studies |
| Group project | 15% | Team report + a Week 11 presentation + peer/contribution review — design or critique a study |
| 5 revision quizzes | 5% | Online (LMS), low-stakes · around Weeks 2, 4, 6, 9 and 12 — confirm the exact weights, dates and exam conditions on your own LMS |
Naming a confounder — the signature short-answer, mark by mark
- +1Name the concept: this is confounding — the claim mistakes a correlation for causation. Ice-cream sales (X) and drownings (Y) move together, but neither causes the other.
- +1Define + identify the confounder: a confounder is a third variable that drives both X and Y. Here it is hot weather (Z): heat raises ice-cream sales and sends more people swimming, so it inflates both counts independently.
- +1Apply it: the X–Y association is therefore spurious — an artefact of the shared cause. Removing the ice-cream vans would not lower drownings, because the link runs through the weather, not through the dessert.
- +1State the fix: control for the confounder — compare drownings against ice-cream sales within the same temperature band (stratify or adjust for weather), or run the comparison only on equally hot days. The raw association should then vanish.
Key terms
- PPDAC cycle
- The investigation cycle that frames almost every critique in this subject: Problem → Plan → Data → Analysis → Conclusion. Most exam prompts are really a question about one node — was the Plan a sound design, were the Data well sampled, is the Conclusion licensed by the design? Walk it from memory and you have a checklist for any study.
- Confounding
- When a third variable drives both the exposure and the outcome, creating an association between them that is not causal. The classic answer to “these two things move together, so one causes the other”: name the confounder, explain how it inflates both, and control for it (stratify, match, restrict or adjust) before believing the link.
- Internal vs external validity
- Internal validity asks whether the study's own conclusion is sound for the people in it (did the design rule out confounding and bias?); external validity asks whether that conclusion generalises beyond them. A tightly controlled RCT can be high on internal validity yet low on external validity if its sample is narrow — the WEIRD-sample problem.
- Sampling bias
- A systematic error in how units are selected, so the sample is unrepresentative of the population in a direction a bigger sample cannot fix. Distinct from sampling error (random, shrinks with size). Includes selection, non-response, undercoverage and voluntary-response bias — and the “who's missing?” reflex is the fastest way to spot it.
- Confidence interval
- A range of plausible values for an unknown population parameter, built so that the procedure captures the true value a stated percentage (e.g. 95%) of the time over repeated samples. It is NOT a 95% probability that the parameter lies in this one interval, and it is NOT a range for individual data points — those two misreads are the most-penalised errors in the inference questions.
MAST20034 FAQ
Is MAST20034 hard?
It is unusual rather than hard: there is no calculator and no calculations, so the difficulty is not arithmetic but reasoning discipline. The challenge is producing a sharp short answer under exam time — naming the right concept (design, bias, confounder, inference rule), defining it in a line, and applying it to a fresh scenario. Students who treat it like a memorise-the-formula subject struggle; the marks live in the ‘because’.
How is MAST20034 assessed?
By four pieces: a 60% short-answer reasoning final, four 200-word individual critique assignments (20% combined), a group project with a Week 11 presentation (15%), and five low-stakes online revision quizzes (5%). The final is in-person and three hours, with no calculator and up to four sides of your own notes carried in. Confirm this year's exact weights, dates and exam conditions on your own LMS.
What is on the MAST20034 final exam?
Short-answer critique prompts across the whole reasoning spine: critique a graph (the five graphics principles), name a study design and say what conclusion is legal, find the confounder in an association, name a sampling method and its bias (including WEIRD), interpret a confidence interval or P-value without the classic misreads, and argue causation across studies with Bradford Hill. Every answer is reasoning in words, never a calculation.
Is the exam open-book, and can I bring a calculator?
It is a restricted bring-in exam, not open-book: you may carry up to four sides — two A4 pages, double-sided — of your own notes. Calculators are not permitted, because no question needs one. So your notes sheet should carry definitions, taxonomies, decision rules and critique checklists, never arithmetic. Always confirm the current bring-in rule on your own LMS, as conditions shift between cohorts.
Is using AskSia for MAST20034 cheating?
No. AskSia is a study reference written in our own words — we host none of your lecturer's files, and the frameworks here (PPDAC, EDA, study-design and sampling taxonomies, NHST and confidence-interval logic, Bradford Hill, data ethics) are standard, published statistical-literacy canon. Every worked critique uses our own invented scenarios, never the assessed case studies. Sia teaches you the method to earn the marks; it does not complete or sit your assessments.
How to study for the exam
Treat this as a critique-skills subject, not a content subject: the same handful of moves recur on fresh scenarios, so drill the moves, not facts. For every prompt, practise the four-part answer shape the markers reward — name the concept → define it in a line → apply it to the scenario → state the consequence or fix. Build your four-side notes sheet as the course runs: definitions, taxonomies (the four observational designs, the sampling methods, the Bradford Hill criteria) and decision rules (the design tree, the graph-critique skeleton, the CI/P-value interpretation rules) — never arithmetic, because there is no calculator. Study design and confounding (the heaviest-marked block) and the name-the-concept decoder are where the exam is won: rehearse spotting the confounder in any association and naming the legal conclusion for any design, until both are automatic.
