Cause and Effect
Cause-and-effect questions test whether you can distinguish a real causal link from a coincidence, a shared third factor, or a sequence of events that merely look related. The PMDC MDCAT 2026 syllabus expects you to recognise causal fallacies, reject weak claims, and decide when an argument's conclusion necessarily follows. Expect 1-2 MCQs from this topic in the Logical Reasoning section.
Causal Reasoning
Causal reasoning is the process of inferring that one event (the cause) brings about another event (the effect). MDCAT items most commonly test the difference between an actual cause and a mere statistical association.
Correlation vs causation
Two variables are correlated when they tend to vary together. They are causally related only when changing one actually produces a change in the other. Ice-cream sales and drowning incidents both rise in summer — they are correlated but neither causes the other; the heat is the real cause.
Necessary vs sufficient causes
A necessary cause must be present for the effect to occur (oxygen is necessary for combustion). A sufficient cause guarantees the effect on its own (decapitation is sufficient for death). Many MDCAT distractors confuse these two: a cause can be necessary without being sufficient, and vice versa.
Latin for "after this, therefore because of this." Assuming that because event B followed event A, A must have caused B. Example: "I wore my lucky shirt and our team won, so the shirt caused the win." Sequence in time alone never proves causation.
Mistaking a correlation for direct causation when both variables are actually driven by a third, hidden factor. Example: Children with bigger feet read better — not because foot size causes literacy, but because both grow with age.
Assuming A causes B when in fact B causes A. Example: "Hospitals make people sick, because hospital patients are sicker than the general population." The reverse is true — sick people seek hospitals.
| Property | Necessary cause | Sufficient cause |
|---|---|---|
| What it means | Effect cannot occur without this cause | Cause alone is enough to produce the effect |
| If cause absent | Effect cannot occur | Effect may still occur (other causes exist) |
| If cause present | Effect may occur (but may not) | Effect will occur |
| Logical form | Effect ⇒ Cause | Cause ⇒ Effect |
| Examples | Oxygen for fire; HIV for AIDS; ATP for muscle contraction | Decapitation for death; full blood-supply cut for tissue death |
| Both? | A cause that is both necessary and sufficient is the only cause: e.g., specific genetic mutation for a single-gene disease. | |
| Fallacy | Pattern | Why it fails | Test it with |
|---|---|---|---|
| Post hoc | "B followed A ∴ A caused B" | Sequence ≠ causation | Could B have happened anyway? |
| Common-cause | A and B correlate ∴ A causes B | Hidden third factor C drives both | What confounder might explain both? |
| Reverse causation | A causes B (when actually B causes A) | Direction of arrow flipped | Could the cause and effect be swapped? |
| Correlation = causation | "X is correlated with Y ∴ X causes Y" | Correlation alone shows nothing about mechanism | Rule out chance, reverse, common cause |
| Anecdotal evidence | One personal story used to refute / prove | Single case ≠ population trend | What does the population data show? |
| Cherry-picking | Selecting only supporting data | Ignores contradicting cases | Was the full data set considered? |
Rejecting False Beliefs
Many everyday claims sound causal but collapse under scrutiny. The MDCAT expects you to recognise weak cause-effect claims and pick them out from a list.
Markers of a weak causal claim
- Relies only on the order of events (post-hoc).
- Cites a single anecdote rather than evidence at population level.
- Ignores plausible alternative explanations.
- Confuses temporary association with stable mechanism.
- Uses vague terms ("linked to", "associated with") and slides into "causes".
Drawing a general causal conclusion from one or two personal stories. Example: "My grandfather smoked all his life and lived to 95, so smoking does not cause cancer." A single counter-example does not overturn population-level evidence.
Selecting only the data points that support the desired causal conclusion while ignoring the rest. The honest test of a cause-effect claim is whether it survives the full data set, not the chosen highlights.
How to test a causal claim
Ask three questions in order: (1) Is the association real or could it be due to chance? (2) Could the direction of cause and effect be reversed? (3) Could a third variable be driving both? Only if all three doubts are resolved is the claim worth accepting.
Valid Arguments
An argument is a set of premises offered in support of a conclusion. Cause-and-effect items often hand you premises and ask whether the conclusion necessarily follows. The two key concepts are validity and soundness.
Deductive validity
An argument is deductively valid when, if the premises are true, the conclusion must be true. Validity is about logical structure, not about whether the premises are actually true.
Soundness
An argument is sound when it is both valid and all of its premises are actually true. A sound argument guarantees a true conclusion. Many valid arguments are unsound because they rest on false premises.
Premise 1: All birds are mammals. Premise 2: A sparrow is a bird. Conclusion: A sparrow is a mammal. The structure is valid — the conclusion follows from the premises — but Premise 1 is false, so the argument is unsound.
Premise 1: All humans are mortal. Premise 2: Socrates is a human. Conclusion: Socrates is mortal. Both premises are true and the conclusion follows necessarily — valid and sound.
- Premise
- A statement offered as a reason or evidence in an argument.
- Conclusion
- The statement that the premises are intended to support.
- Valid argument
- One whose conclusion must be true if its premises are true (form-correct).
- Sound argument
- A valid argument whose premises are also actually true.
- Cogent argument
- An inductively strong argument with true premises — the inductive counterpart to soundness.
Worked MCQs
Five MCQs that capture the high-yield testing patterns for cause and effect. Read the explanation even when you get the answer right — it's where the deeper concept lives.
Q1. A study finds that towns with more churches also have more bars. The most reasonable explanation is:
This is a textbook common-cause situation. Larger towns simply have more of every kind of building — churches, bars, schools, shops. Concluding that one causes the other is a fallacy because both are driven by a third variable: population.
Q2. "I drank a glass of warm milk last night and slept well, so warm milk cures insomnia." This argument commits which fallacy?
The arguer infers causation purely from temporal sequence (B happened after A). One personal experience cannot establish a general cause-effect link, especially without ruling out chance or other causes (tiredness, time of day, etc.).
Q3. Premise 1: All metals expand on heating. Premise 2: Iron is a metal. Conclusion: Iron expands on heating. This argument is:
The conclusion follows necessarily from the premises (validity), and both premises are factually true (soundness). A valid argument with true premises is the gold standard — sound.
Q4. Oxygen is required for combustion to occur, but oxygen alone does not start a fire. Oxygen is therefore a:
Without oxygen, combustion cannot occur — so it is necessary. But oxygen on its own does not ignite anything — you also need fuel and an ignition source — so it is not sufficient.
Q5. Statement: "Patients who visit hospitals frequently die earlier than those who do not, so hospitals shorten lives." The flaw in this reasoning is:
The arguer has the cause and effect backwards. People who visit hospitals frequently are usually already sick — their illness is the cause both of hospital visits and of earlier death. The hospital is not shortening their life; their illness is.
Quick Recap
- Correlation never proves causation — rule out chance, reverse causation, and a third common cause.
- Post-hoc fallacy: "after this, therefore because of this" — sequence alone is not enough.
- Necessary cause must be present for the effect; sufficient cause alone produces it.
- A valid argument has the right structure; a sound argument is valid and has true premises.
- Reject weak causal claims that rely on anecdote, cherry-picked data, or vague "linked to" wording.
- Use the C-R-A-P screen before accepting any cause-effect statement.