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🔬 Science · Scientific Reasoning · Lesson 5 of 6 · 5 min

Logic and evidence: correlation vs causation, observation vs inference

🧠 Two things happening together does not mean one causes the other. TEAS items test whether you can spot that leap.

💡 Key idea

Correlation shows variables move together; only a controlled experiment can show one causes the other.

🧠 The idea

An OBSERVATION is information gathered directly with the senses or instruments ("the solution turned blue"). An INFERENCE is a conclusion or interpretation based on observations ("a chemical reaction occurred"). Observations can be QUALITATIVE (descriptions: color, smell, texture) or QUANTITATIVE (numbers with units: 25 mL, 37 °C). A CORRELATION means two variables change together; it can be positive (both rise) or negative (one rises as the other falls). CAUSATION means one variable actually produces a change in the other. Correlation alone does not prove causation, because a third factor may drive both, the direction may be reversed, or the link may be coincidence. Ice cream sales and sunburns both rise in summer because of a third factor: sunny, hot weather. A controlled experiment that changes only one variable is the best evidence for cause and effect. Strong evidence is measurable, repeatable and comes from adequate samples.

✏️ Worked example

A survey finds that people who carry lighters have higher rates of lung disease. Does carrying a lighter cause lung disease? Ask three questions. Third factor? Yes: smoking explains both carrying a lighter and lung disease. Reversed direction? No. Coincidence? Unlikely with a large sample. Conclusion: the data show a correlation, and the likely cause is a third variable, smoking. To test causation you would need a controlled experiment, which here would be unethical, so researchers use careful study designs that account for smoking.

📌 Takeaways

  • Observation = what you sense or measure; inference = what you conclude from it.
  • Qualitative = descriptions; quantitative = numbers with units.
  • Correlation is not causation: look for a third factor or reversed direction.

📖 Terms in this lesson

Correlation vs causation: Two things rising or falling together (correlation) does not prove that one causes the other (causation); for example, ice cream sales and sunburns both rise in summer, but neither causes the other.

✅ Check yourself

Question 1 of 3

Which statement is an inference rather than an observation?

  1. The leaf is sick from a fungus.
  2. The leaf feels dry and brittle.
  3. The leaf has brown spots.
  4. The leaf is 6 cm long.
Show the answer and rationale

Answer: A

Saying the leaf is sick from a fungus is an explanation drawn from what was seen, so it is an inference. Length, brown spots and a dry feel are all gathered directly by measuring, looking or touching.

Question 2 of 3

A town finds that months with more umbrella sales also have more car accidents. What is the most likely explanation?

  1. Umbrellas cause drivers to crash.
  2. Car accidents cause people to buy umbrellas.
  3. Rainy weather increases both.
  4. The two numbers are not related at all.
Show the answer and rationale

Answer: C

Rain is a third factor that raises both umbrella sales and accidents (wet roads, poor visibility). The data show a real correlation, so "not related" is wrong, and neither variable directly causes the other.

Question 3 of 3

Which observation is quantitative?

  1. The water is cloudy.
  2. The water's temperature is 18 °C.
  3. The water is light green.
  4. The water smells like sulfur.
Show the answer and rationale

Answer: B

Quantitative observations are numbers with units, such as 18 °C. Cloudy, sulfur smell and light green are descriptions of qualities, so they are qualitative.

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