Drawing Conclusions and Evaluating Evidence — ACT Science

Introduction

Conclusions are the most tempting place to use outside knowledge on ACT Science — and the most dangerous. A valid conclusion must follow from the data given. Everything else is speculation.

Conclusion evaluation questions appear in every passage type and represent the highest-level thinking on ACT Science — distinguishing 28–30 scorers from 30–36 scorers.

By the end of this lesson you will be able to:

Identify conclusions fully supported by data versus those that go beyond the data
Evaluate whether evidence strengthens, weakens, or is irrelevant to a conclusion
Recognize the difference between correlation and causation

You will evaluate four conclusions about a climate dataset — identifying which is supported, which over-reaches, and which confuses correlation with causation.

The Concept

The Core Rule

A valid conclusion must be supported entirely by the data presented. Any conclusion requiring outside knowledge, assuming causation from correlation, or generalizing beyond tested conditions is NOT supported — even if scientifically accurate in real life.

How the ACT tests this

Supported conclusion selection: 'Which conclusion is best supported by Table 2?'
Evidence evaluation: 'Which finding would most weaken the researcher's conclusion?'
Correlation vs. causation: 'Does the data support that CO₂ causes higher temperatures?'

What Makes a Conclusion Valid

A valid conclusion describes what the data shows without requiring additional assumptions. Invalid if it: extends beyond tested range, introduces untested variables, assumes causation from correlation, or requires outside knowledge.

Valid: 'At 20–40°C, higher temperature is associated with higher reaction rate for Enzyme A'
Invalid: 'Enzyme A would function better than Enzyme B in the human body' — outside knowledge
Key test: can you point to this in the figure?

Strengthening and Weakening Evidence

Strengthening: confirms key assumption or extends support to new conditions. Weakening: undermines a key assumption or provides an alternative explanation.

Strengthens: same trend under new conditions, rules out alternatives
Weakens: exception to the pattern, alternative cause
Irrelevant: measures a different variable than the conclusion

Correlation vs. Causation

Correlation: two variables change together. Causation: one directly produces change in the other. ACT Science never establishes causation from observational data alone.

Correlation: 'as X increases, Y also increases' — acceptable from data
Causation: 'X causes Y' — only valid with controlled experiment and stated mechanism
Classic trap: CO₂ and temperature both rise (correlation) does not establish which causes which

Your strategy

Step 1 — Identify the conclusion's key claim: what variable, what direction, how strong?
Step 2 — Find the data it refers to. Can you point to it in the figure?
Step 3 — Check scope: does it stay within tested range and conditions?
Step 4 — Check causal language: if it says 'causes,' verify controlled experiment and stated mechanism.

Worked Examples

Easy Example 1 Option A Matches Common Sense — Heat Makes People Buy Ice Cream. But Common Sense Is Outside Knowledge. Data Shows Correlation, Not Causation.

Table 1 tracks daily temperature (°C) and ice cream sales (units/day) in one city over 30 summer days.

Table 1: 25°C=150, 28°C=210, 31°C=280, 34°C=350, 37°C=410 units/day.

Which conclusion is best supported by Table 1?

A. Higher temperatures cause people to buy more ice cream
B. Ice cream sales are associated with higher daily temperatures in this city during summer (Correct answer)
C. Sales would continue to increase if temperatures reached 50°C
D. Temperature is the only factor determining sales

Step 1

Step 1 — Table 1 shows correlation: as temperature increases, sales increase.

Step 2

Step 2 — Option A: causal language without a controlled experiment. Invalid.

Step 3

Step 3 — Option B: 'associated with' = correlation language. Within tested range. City-specific. Supported.

Step 4

Step 4 — C extrapolates beyond 37°C; D claims exclusivity. Answer: B.

Correct answer: B

Why B is correct

Accurate correlation within tested conditions. Correct.

Why other options are wrong

A: Causal language without controlled experiment. Incorrect.

C: 50°C outside tested range (25–37°C). Incorrect.

D: Claims 'only factor' — not supported by data. Incorrect.

⚠ Trap: Option A matches common sense — heat makes people buy ice cream. But common sense is outside knowledge. Data shows correlation, not causation.

Medium Example 2 Option C Is Tempting Because It Introduces An Alternative Cause. But C Doesn't Address The UV-activity Relationship In This Experiment Directly — B Does.

Experiment measures UV exposure effect on DNA repair enzyme activity. Three groups: 0, 4, 8 hours UV/day for 2 weeks.

Week 1: 0hr=10, 4hr=18, 8hr=27 units. Week 2: 0hr=11, 4hr=22, 8hr=35 units. All increase slightly week over week.

Researcher concludes: 'UV light increases DNA repair enzyme activity.' Which finding would most WEAKEN this conclusion?

A. Same trend found in mouse skin cells
B. Adding a UV blocker equalizes activity across all groups, eliminating differences (Correct answer)
C. Enzyme activity also increases with temperature
D. The 8-hour group had more activity in Week 3 than Week 2

Step 1

Step 1 — Conclusion depends on UV being the cause of activity differences.

Step 2

Step 2 — A weakening finding must show UV is not actually driving the difference.

Step 3

Step 3 — Option B: blocking UV eliminates group differences. This directly challenges whether UV causes the divergence.

Step 4

Step 4 — Answer: B.

Correct answer: B

Why B is correct

Blocking UV eliminates differences — strongest challenge to the UV-activity relationship. Correct.

Why other options are wrong

A: Replication in mice strengthens, not weakens. Incorrect.

C: Temperature as alternative cause weakens but less directly than B. Incorrect.

D: More activity over time supports the conclusion. Incorrect.

⚠ Trap: Option C is tempting because it introduces an alternative cause. But C doesn't address the UV-activity relationship in this experiment directly — B does.

Hard Example 3 Students With Physics Knowledge About Melting Points May Choose C For The Wrong Reason. Correct Reason: Data Simply Doesn't Extend Beyond 80°C.

Researcher concludes: 'All metals show increased resistance at higher temperatures, and this trend would continue indefinitely beyond 80°C.' Data covers 20–80°C only.

Figure 1: Copper, Aluminum, Iron — all show linear resistance increase from 20°C to 80°C.

Which part of the conclusion is NOT supported by Figure 1?

A. All three metals show increased resistance at higher temperatures
B. The trend is linear within 20–80°C
C. The trend would continue indefinitely beyond 80°C (Correct answer)
D. Copper has lower resistance than Iron at all tested temperatures

Step 1

Step 1 — Break conclusion into parts: (1) all metals increase, (2) continues indefinitely beyond 80°C.

Step 2

Step 2 — Figure 1 shows increasing trend from 20–80°C. Part 1 supported.

Step 3

Step 3 — 'Continues indefinitely beyond 80°C' — data ends at 80°C. No data beyond this range.

Step 4

Step 4 — Indefinite extrapolation is unsupported. Answer: C.

Correct answer: C

Why C is correct

Data ends at 80°C. Claiming indefinite continuation is an unsupported extrapolation. Correct.

Why other options are wrong

A: All three lines show upward trends in the tested range. Supported. Incorrect.

B: All three lines are linear within the range. Supported. Incorrect.

D: Copper always below Iron in the figure. Supported. Incorrect.

⚠ Trap: Students with physics knowledge about melting points may choose C for the wrong reason. Correct reason: data simply doesn't extend beyond 80°C.

Strategy Tips

Eliminate answers with causal language, extrapolations beyond tested range, or 'only/always/never' claims
For weakening: identify the conclusion's key assumption — the correct weakener attacks that assumption
Correlation language ('associated with') is almost always correct for observational data
A conclusion saying 'always' or 'in all cases' is almost always wrong
For strengthening/weakening: classify each option as same trend (strengthens), opposite (weakens), alternative explanation (weakens), or irrelevant

Common pitfalls

Choosing a 'scientifically true' conclusion not supported by the given data

Confusing correlation with causation when no controlled experiment is described

Accepting extrapolations beyond the tested range regardless of physical laws

Ask 'can I point to this in the figure?' for each answer choice. If yes, it is supported. This takes 90 seconds but is worth doing carefully.

Summary

Valid conclusions are bounded by the data — same scope, range, and conditions, nothing more
Correlation never implies causation without a controlled experiment
Strengthening evidence confirms the key assumption; weakening undermines it or offers an alternative

Find a conclusion in any science article ('eating X leads to Y'). Evaluate: causal or correlational? Within tested conditions? What single finding would weaken it?

Next: Conflicting Viewpoints Passage All ACT Science lessons