Hypotheses, Predictions, and Modifying Experiments — ACT Science

Introduction

A hypothesis is a testable prediction, not a fact. ACT Science does not care whether you know the correct answer in real life — it cares whether you can identify which prediction the given data supports or refutes.

Hypothesis and prediction questions appear on every ACT Science test, typically 3–5 questions. They are often the hardest in a passage but fully solvable with the right framework.

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

Distinguish between a hypothesis, a prediction, and a conclusion
Evaluate whether given data supports, refutes, or is inconclusive with respect to a stated hypothesis
Propose a valid experiment modification to test a new hypothesis

You will evaluate two competing predictions about bacterial growth, determine which the data supports, and propose a modification to test an untested claim — all without biology knowledge beyond the passage.

The Concept

The Core Rule

Support or refutation is decided by comparing the prediction to the data — never by whether the hypothesis is scientifically correct. A hypothesis predicting X is supported if the data shows X.

How the ACT tests this

Evaluation: 'Do the results support or refute Hypothesis 1? Why?'
Prediction: 'If the hypothesis is correct, what would be expected at 50°C?'
Modification: 'What additional trial would best allow testing whether pH affects the result independent of temperature?'

Hypothesis vs. Prediction vs. Conclusion

Hypothesis: proposed explanation stated before data collection. Prediction: specific measurable outcome if hypothesis is true. Conclusion: judgment after examining data.

Hypothesis: 'Enzyme X is more active at higher temperatures'
Prediction: 'If true, Enzyme X will show higher rates at 40°C than 20°C'
Conclusion: 'Data support/refute the hypothesis because…'

Evaluating Support vs. Refutation

Translate the hypothesis into a direction word (increases/decreases/peaks/flat) and compare to actual data trend.

Support: trend matches hypothesis direction
Refute: trend is opposite or absent
Inconclusive: relevant variable not tested

Proposing Valid Modifications

Identify the new IV, ensure it is the only thing that changes, confirm the DV remains measurable.

Name the new IV
Propose a trial where only that IV changes
Include a baseline comparison condition

Your strategy

Step 1 — Find the hypothesis and underline its direction word (increases/decreases/no effect).
Step 2 — Find the relevant data figure.
Step 3 — Compare directions: match=support, opposite=refute, no data=inconclusive.
Step 4 — For modification: name new IV, one new trial, only that variable changes.

Worked Examples

Easy Example 1 Option D: Students Who Know Bacteria Have Growth Limits May Second-guess The Data. The Data Shows What It Shows.

Researcher hypothesizes that increasing nutrient concentration increases bacterial colony count after 24 hours.

Table 1: 0 mg/mL=5, 2 mg/mL=18, 4 mg/mL=34, 8 mg/mL=61 colonies.

Do the results in Table 1 support or refute the hypothesis?

A. Support; colony count increased as concentration increased (Correct answer)
B. Refute; colony count decreased
C. Support; concentration stayed constant
D. Refute; 61 colonies is too many for nutrients alone

Step 1

Step 1 — Hypothesis direction: increasing concentration → increasing colony count.

Step 2

Step 2 — Table 1: 5→18→34→61 as concentration rises. Clearly increasing.

Step 3

Step 3 — Trend matches hypothesis direction → support.

Step 4

Step 4 — Answer: A.

Correct answer: A

Why A is correct

Count increases with concentration, matching the hypothesis. Correct.

Why other options are wrong

B: Count did not decrease. Incorrect.

C: Concentration was the IV, not constant. Incorrect.

D: Outside-knowledge reasoning. Incorrect.

⚠ Trap: Option D: students who know bacteria have growth limits may second-guess the data. The data shows what it shows.

Medium Example 2 Option B Correctly Describes The Data But Applies Equally To Both Hypotheses — Students Stop At 'decreasing' Without Checking The Rate Of Decrease.

Scientist 1 hypothesizes B = k/r (halves when distance doubles). Scientist 2 hypothesizes B = k/r² (quarters when distance doubles). Figure 1 shows field strength vs. distance.

Data: 1cm=40μT, 2cm=20μT, 3cm=13.3μT, 4cm=10μT, 5cm=8μT. Values halve when distance doubles.

Based on Figure 1, which scientist's hypothesis is better supported?

A. Scientist 1, because field strength halves when distance doubles (Correct answer)
B. Scientist 2, because field strength decreases as distance increases
C. Scientist 1, because field strength reaches zero at large distances
D. Scientist 2, because the decrease is rapid near the wire

Step 1

Step 1 — Scientist 1 predicts 1/r: doubling distance halves B. Scientist 2 predicts 1/r²: doubling quarters B.

Step 2

Step 2 — Check 1→2 cm: 40→20. That is halving. Check 2→4 cm: 20→10. Also halving when distance doubles.

Step 3

Step 3 — If Scientist 2 correct: doubling should quarter B: 40→10 at 2cm. Data shows 20, not 10.

Step 4

Step 4 — Data matches Scientist 1's 1/r model. Answer: A.

Correct answer: A

Why A is correct

Halving when distance doubles = 1/r = Scientist 1. Data confirms. Correct.

Why other options are wrong

B: 'Decreasing' applies to both hypotheses — doesn't distinguish. Incorrect.

C: Data doesn't show B reaching zero. Incorrect.

D: Rapid decrease near wire is also consistent with Scientist 1. Incorrect.

⚠ Trap: Option B correctly describes the data but applies equally to both hypotheses — students stop at 'decreasing' without checking the rate of decrease.

Hard Example 3 'More Is Better' Trap: Option A Feels More Thorough But The Hypothesis Concerns Only The Optimal Temperature. Minimal Valid Test Is Cleanest.

Current experiment varies temperature (20°C, 40°C, 60°C) at pH 7.0, concentration 0.5M. Researcher now hypothesizes pH 5.0 at optimal temperature increases yield further. Optimal temperature = 40°C (72% yield).

Table 1: 20°C=45%, 40°C=72%, 60°C=58%.

Which modification best tests the new pH hypothesis?

A. Run pH 5.0 trials at all temperatures
B. Run one trial at pH 5.0, 40°C, 0.5M and compare to existing 40°C pH 7.0 result (Correct answer)
C. Change both pH to 5.0 and concentration to 1.0M at 40°C
D. Run pH 5.0 and pH 3.0 simultaneously at 40°C and 60°C

Step 1

Step 1 — Hypothesis: pH 5.0 at 40°C increases yield. New IV = pH. Hold temperature at 40°C, concentration at 0.5M.

Step 2

Step 2 — Need comparison: pH 5.0 vs pH 7.0 at 40°C. Existing 40°C, pH 7.0 result = 72% baseline.

Step 3

Step 3 — Option B adds exactly one new condition: pH 5.0 at 40°C, 0.5M. Only pH changes.

Step 4

Step 4 — Answer: B.

Correct answer: B

Why B is correct

One new trial, only pH changes, direct comparison to existing baseline. Correct.

Why other options are wrong

A: Running all temperatures at pH 5.0 is more than needed and introduces temperature as a second variable. Over-specified. Incorrect.

C: Changing both pH and concentration confounds the test. Incorrect.

D: Adding pH 3.0 and 60°C introduces variables beyond the hypothesis. Incorrect.

⚠ Trap: 'More is better' trap: Option A feels more thorough but the hypothesis concerns only the optimal temperature. Minimal valid test is cleanest.

Strategy Tips

Underline the direction word in every hypothesis before evaluating
Translate data trend into one direction word, compare to hypothesis direction word
For modifications: identify the one new variable and propose a trial where only that changes
Mixed results → 'partially supports' — never force a clean support/refute
Predictions = 'if-then' statements: 'If hypothesis X, then at condition Y, result Z'

Common pitfalls

Evaluating hypothesis based on scientific correctness rather than the given data

Confusing 'consistent with' (support) with 'proves'

Modification proposals that alter two variables simultaneously

Hypothesis evaluation takes 60–90 seconds — do not rush the hypothesis-to-data comparison.

Summary

Support/refute is determined by comparing hypothesis direction to data trend
Supported = trend matches; refuted = trend opposes; inconclusive = data doesn't address it
Valid modifications add exactly one new variable while holding all others constant

Read any science article claim. Write it as a hypothesis, generate a prediction, identify what data would support vs. refute it.

Next: Drawing Conclusions and Evaluating Evidence All ACT Science lessons