Research Summaries

Experimental design, variables and controls, comparing experiments and evaluating conclusions.

Worked Examples

<details> <summary><b>Example 1: Label every part of a procedure</b></summary>

Procedure: A student placed 2.0 g of yeast in each of four flasks containing 100 mL of water. The water in the flasks contained 0%, 2%, 4%, or 6% sugar. All flasks were kept at 30 °C. She collected the gas released by each flask for 20 minutes and recorded its volume in milliliters.

Solution:

1. What did she pick? The sugar percentage (0, 2, 4, 6) → IV.
2. What did she record? The volume of gas → DV.
3. What stayed the same? Yeast mass (2.0 g), water volume (100 mL), temperature (30 °C), collection time (20 min) → constants.
4. Which flask is the baseline? The 0% sugar flask → control. It shows how much gas the yeast releases with no added sugar.

ACT skill: Underline numbers that repeat in every trial (constants) and numbers that change (the IV).

</details> <details> <summary><b>Example 2: Which hypothesis was the study testing?</b></summary>

Question: Using the yeast study above, which hypothesis was the study designed to test?

• Yeast releases more gas at higher temperatures.
• Yeast releases more gas when more sugar is available.
• Larger amounts of yeast release more gas.
• Yeast releases more gas in larger volumes of water.

Solution: The study varied only sugar percentage and measured gas, so the hypothesis must link sugar to gas: "Yeast releases more gas when more sugar is available." Temperature, yeast mass, and water volume were all held constant, so no hypothesis about them could be tested here.

</details>

Worked Examples

<details> <summary><b>Example 1: Find the confound and fix it</b></summary>

Study: A student wants to know whether music genre affects typing speed. She types for 5 minutes with rock music on Monday morning and 5 minutes with classical music on Friday evening, one trial each.

Solution:

1. Variables that differ between the two sessions: genre (intended IV), day, and time of day → confounds.
2. Only one trial per genre → no way to tell a real difference from a lucky or unlucky session.
3. Best fix: test both genres at the same time of day, several times each, and compare the averages.

ACT skill: The best improvement removes the extra variable and adds repetition; a choice that does only one of these is weaker if the other option exists.

</details> <details> <summary><b>Example 2: Which result is more reliable?</b></summary>

Study: Lab A tests a new hand lotion on 6 volunteers and finds skin moisture rises by 12%. Lab B uses the same procedure on 300 volunteers and finds a 4% rise.

Solution: Lab B's result is more reliable. With only 6 people, one or two unusual volunteers can push the average far from the true effect. A large sample averages out individual differences, so 4% is the better estimate. A bigger effect in a smaller study does not make that study more convincing.

</details>

Worked Examples

<details> <summary><b>Example 1: What changed between the experiments?</b></summary>

Passage summary: In Experiment 1, a student dropped one rubber ball from heights of 0.5, 1.0, and 1.5 m and measured how high it bounced. In Experiment 2, she dropped balls made of rubber, plastic, and foam, all with the same diameter, from 1.0 m.

Question: Which variable was tested in Experiment 2, and which variable from Experiment 1 became a constant?

Solution: Experiment 2 changed the ball material (new IV). Drop height, the IV of Experiment 1, was fixed at 1.0 m (now a constant). Bounce height was the DV in both experiments, and ball diameter was held the same.

</details> <details> <summary><b>Example 2: Testing a hypothesis with the right table</b></summary>

Data: Experiment 1 (all trays given 10 mL of water per day): 15 °C → 40%, 20 °C → 65%, 25 °C → 85%, 30 °C → 70% germination. Experiment 2 (all trays at 25 °C): 5 mL → 50%, 10 mL → 85%, 15 mL → 80%, 20 mL → 45%.

Question: Do the results support the hypothesis that germination increases steadily as more water is supplied?

Solution:

1. Water is varied only in Experiment 2, so use that table.
2. Germination rises from 50% to 85% (5 → 10 mL) but then falls to 80% and 45%.
3. A steady increase is not supported. The highest germination in either table, 85%, is the shared condition: 25 °C with 10 mL per day.

</details>

Worked Examples

<details> <summary><b>Example 1: Support one viewpoint but not the other</b></summary>

Viewpoints: Student 1 says a wool sweater keeps you warm because the wool itself produces heat. Student 2 says the sweater produces no heat; it slows the loss of heat your body produces.

Question: Which finding would support Student 2 but not Student 1?

• A person wearing the sweater feels warmer than without it.
• A thermometer wrapped in the sweater, with no person inside, stays at room temperature.
• The sweater feels warm right after it is taken off.
• Wool sweaters are thicker than cotton shirts.

Solution: Both students agree that the sweater makes a person feel warmer, so that finding cannot separate them. If wool produced heat, a thermometer wrapped in it should warm up. The thermometer staying at room temperature contradicts Student 1 and fits Student 2. A sweater feeling warm after use fits both (it held body heat, or it made heat), and thickness is not part of either claim.

</details> <details> <summary><b>Example 2: A finding that sorts three viewpoints</b></summary>

Viewpoints: Three hypotheses explain why a lizard species is darker in the mountains than in the lowlands. H1: dark color absorbs more sunlight in cold air. H2: dark color hides lizards from predators on dark mountain rock. H3: color is set by diet, and mountain insects contain a darkening pigment.

Finding: Lowland lizards raised in the lab on mountain insects stayed light-colored.

Solution: H3 predicts that eating mountain insects darkens the lizards, so this finding weakens H3. H1 and H2 say nothing about diet, so the finding neither supports nor weakens them.

</details>

Worked Examples

<details> <summary><b>Example 1: Extrapolation beyond the data</b></summary>

Data: A reaction ran at 2 mmol/min at 10 °C, 4 mmol/min at 20 °C, and 8 mmol/min at 30 °C. A researcher concluded that the rate is certain to be 64 mmol/min at 60 °C.

Solution:

1. Within the data, the rate doubles every 10 °C, so the pattern itself is real.
2. No trials were run above 30 °C. Many processes level off or reverse at high temperatures (an enzyme, for example, can stop working).
3. Evaluation: the conclusion goes beyond the data. A prediction at 60 °C could be an estimate, but not a certainty.

</details> <details> <summary><b>Example 2: Yes/No with the right reason</b></summary>

Data: Experiment 1 (magnet touching the clips): magnets of strength 1, 2, and 3 units lifted 5, 10, and 15 paper clips. Experiment 2 (strength 2 magnet): held 1, 2, and 3 cm from the clips, it lifted 10, 4, and 1 clips.

Claim: "The number of clips lifted depends only on magnet strength."

Solution: Experiment 2 held strength constant, yet the number of clips changed with distance. So the answer is No, because the clips lifted also changed with distance. "No, because the clips fell as strength rose" has the right yes/no but a false reason, since clips rose with strength.

</details>

Worked Examples

<details> <summary><b>Example 1: Combine two tables</b></summary>

Data: Experiment 1 (1 bulb): a light sensor read 400 units at 1 m, 100 at 2 m, and 25 at 4 m. Experiment 2 (sensor at 1 m): 1, 2, and 3 bulbs gave 400, 800, and 1,200 units.

Question: Predict the reading for 3 bulbs at 2 m.

Solution:

1. Shared condition: 1 bulb at 1 m → 400 in both tables.
2. From Experiment 1, moving from 1 m to 2 m divides the reading by 4.
3. From Experiment 2, 3 bulbs at 1 m gives 1,200.
4. 3 bulbs at 2 m ≈ 1,200 ÷ 4 = 300 units.

</details> <details> <summary><b>Example 2: Explain why two studies disagree</b></summary>

Studies: Study A found that Fertilizer N increased lettuce growth by 30%. Study B, using the same fertilizer dose, found no increase.

Procedural differences: Study A used sandy soil low in nitrogen; Study B used soil already rich in nitrogen. Study A measured growth after 30 days; Study B measured after 32 days.

Solution: A 2-day difference in measurement time is unlikely to erase a 30% effect. Soil that already contains plenty of nitrogen would leave little room for a nitrogen fertilizer to help, so the soil difference best explains the conflicting results.

</details>

⏱️ Timed Research Summary Passage

Part 7 of 7 — Putting It All Together Under Enhanced ACT Timing

This part pulls every skill from Parts 1–6 into one full Research Summaries passage, worked under real timing.

The timing you are working with

One minute per question includes the time spent reading the passage. A passage with 8 questions therefore gets about 8 minutes total, not 8 minutes plus reading time. That is why the reading routine below is short.

A 90-second passage routine

1. Introduction (15 seconds): what question are the researchers asking? Write it in a few words.
2. Each experiment (20–25 seconds): label the IV, DV, and constants in the margin. For "repeated except…" experiments, write only what changed.
3. Tables (10 seconds each): read the headings and units, and note the overall trend (up, down, or up-then-down). Do not study every number.
4. Go to the questions. Return to the passage only for the specific number or sentence a question needs.

The question types you will meet, and where you learned them

Triage: which questions to do first

• Fast (about 30 seconds): identify a variable, read a value, find the highest or lowest result. Do these immediately.
• Medium (about 1 minute): trends, "how did Experiment 2 differ," interpolation.
• Slow (up to 2 minutes): combining experiments, evaluating a conclusion with "Yes, because / No, because" choices, designing a new trial.

If a question is taking more than 2 minutes, eliminate what you can, choose an answer, mark it, and move on. Saved seconds from the fast questions pay for the slow ones.

Elimination habits that work on every question

• Cross out choices that quote a true fact from the wrong experiment.
• Cross out choices that use absolute words ("all," "proves," "exactly") about untested cases.
• In "Yes/No, because" questions, decide yes or no first, then compare only the two remaining reasons.
• In "supports X but not Y" questions, cross out any finding both viewpoints already accept.

Replication inside a passage

Researchers often run several dishes, plants, or trials per condition and report the mean. When individual trials are shown, look at how much they vary. If three dishes in one condition gave 83%, 86%, and 83%, the mean of 84% is trustworthy. If they gave 40%, 84%, and 128 eggs out of 200, something is wrong with the measurement. A single trial per condition is a weakness: the result could be a fluke, and repeating it would make it more reliable.

Now try the passage

Set a timer for 8 minutes and answer all 8 questions in the two practice sets below without stopping. Then read every explanation, including those for questions you got right, and note which Part each mistake came from.