Drawing Conclusions & Evaluating Claims
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ACT Science › Drawing Conclusions & Evaluating Claims
A student dissolves 50 g of KNO₃ in 100 g of water at 40°C. Based on Figure 1, the resulting solution would be best described as:
unsaturated, because 50 g is less than the maximum solubility of 60 g at 40°C.
supersaturated, because 50 g is greater than the maximum solubility at 40°C.
saturated, because 50 g is exactly the maximum solubility at 40°C.
dilute, because KNO₃ is insoluble at 40°C.
Explanation
This is a concept application question requiring you to understand solubility definitions and apply them to graph data. According to Figure 1, KNO₃ has a solubility of approximately 60 g/100 g H₂O at 40°C. This means up to 60 g can dissolve at this temperature. Since the student only dissolved 50 g, which is less than the maximum of 60 g, more could still dissolve. By definition, this makes the solution unsaturated (not yet at maximum capacity). Choice B is correct. Choice A (saturated) would only be true if exactly 60 g were dissolved. Choice C (supersaturated) would require dissolving MORE than the maximum, which typically requires special cooling techniques. Choice D (dilute/insoluble) is nonsensical—the graph clearly shows KNO₃ does dissolve at 40°C. Pro tip: Saturated = at maximum; Unsaturated = below maximum; Supersaturated = above maximum (unstable).
A city tested a new bus-lane policy intended to reduce commute times. Commute times (minutes) were recorded for 30 randomly selected bus riders one week before implementation and for 30 bus riders one week after. The riders before and after were not necessarily the same individuals. Weather conditions differed: the “after” week had heavier rain on most days.
Table 1 shows the mean commute times. The author concluded: “The bus-lane policy increased commute times.”
Which of the following is a flaw in the author’s reasoning?
The conclusion ignores a potential confounder: heavier rain could increase commute times independent of the policy.
The conclusion is flawed because commute time cannot be measured in minutes.
The conclusion is flawed because using different riders before and after always eliminates confounding variables.
The conclusion is flawed because a larger mean after implementation must indicate improved commutes.
Explanation
The flaw in the author's reasoning is ignoring a potential confounding variable: weather conditions. The data show longer mean commute times after the bus-lane policy implementation, but the "after" week had heavier rain on most days compared to the "before" week. Heavy rain typically increases traffic congestion and slows all vehicles, including buses, independent of any lane policy. Without controlling for weather conditions or comparing similar weather days, we cannot determine whether the increased commute times were due to the policy or the rain. The conclusion incorrectly attributes the entire effect to the policy while ignoring this obvious alternative explanation.
Suppose a new survey of the Milky Way's halo reveals a vast population of billions of rogue planets and brown dwarfs, totaling 5 times the mass of all visible stars. This finding would strictly support the hypothesis of:
Scientist 2.
both Scientist 1 and Scientist 3.
Scientist 3.
Scientist 1.
Explanation
This is a prediction/evidence evaluation question. Scientist 2 explicitly proposes that dark matter consists of MACHOs: "black holes, neutron stars, brown dwarfs (failed stars), and rogue planets." Finding billions of rogue planets and brown dwarfs would directly confirm Scientist 2's hypothesis. Choice B is correct. Choice A (Scientist 1) proposes WIMPs (exotic particles), not normal matter objects. Choice C (Scientist 3) rejects the existence of missing mass entirely. Choice D is illogical—Scientists 1 and 3 have opposing views. Pro tip: Match new evidence to the specific prediction each hypothesis makes.
A geophysicist claims that the "shadow zone" (an area where no seismic waves are detected) occurs because P-waves are bent (refracted) by the sudden change in density at the core-mantle boundary. Do the data in Figure 1 and Figure 2 support the idea that there is a sudden change in material properties at this boundary?
Yes, because the temperature drops to zero at 2,900 km.
No, because the density decreases at the boundary.
No, because P-wave velocity remains constant across the boundary.
Yes, because both velocity and density change abruptly at 2,900 km.
Explanation
This is a claim evaluation question requiring you to check whether data support a statement. The claim mentions "sudden change in density at the core-mantle boundary." Looking at 2,900 km: Figure 1 shows P-wave velocity drops sharply from 13 to 8 km/s (sudden change in velocity), and Figure 2 shows density jumps from 5.5 to 10.0 g/cm³ (sudden change in density). These abrupt discontinuities support the claim of sudden material property changes. Choice A is correct. Choice B mentions temperature, which isn't shown in either figure. Choice C is factually wrong—velocity changes dramatically. Choice D is factually wrong—density increases, not decreases. Pro tip: For support questions, verify whether the data actually show what the claim describes.
Which of the following statements best explains the trend for the Mouse in Study 1 (Figure 1)?
At lower temperatures, the mouse must consume more oxygen to generate heat and maintain its body temperature.
The mouse's enzymes function more efficiently at 5°C than at 25°C.
At higher temperatures, the mouse becomes more active, requiring more oxygen.
The mouse enters a state of hibernation as the temperature drops.
Explanation
This is a scientific reasoning question asking you to explain observed data using biological principles. The Introduction defines endotherms as animals that "generate their own body heat to maintain a constant internal temperature." At cold temperatures (5°C), the mouse must burn more energy (consume more O₂) to maintain its internal temperature against the cold environment. At 25°C (thermoneutral zone), less energy is needed because ambient temperature is closer to body temperature. This explains why metabolic rate is high at 5°C and drops to minimum at 25°C. Choice A correctly explains this thermoregulation principle. Choice B (more active at high temp) contradicts that animals were "kept at rest." Choice C (enzymes more efficient at 5°C) is backwards—enzyme efficiency typically increases with temperature up to an optimal point. Choice D (hibernation) contradicts the high metabolic rate shown. Pro tip: Connect data patterns to biological definitions provided in the introduction.
A student hypothesized that increasing the concentration of NaHCO₃ indefinitely will continue to increase the rate of photosynthesis linearly. Do the results of Study 3 support this hypothesis?
Yes; the rate increased from 2 to 61 bubbles as concentration increased.
Yes; the rate doubled between Trial 7 and Trial 8.
No; the rate decreased after Trial 8.
No; the rate plateaued (leveled off) between Trial 9 and Trial 10.
Explanation
This is a hypothesis evaluation question. The hypothesis claims "linear" increase means the rate should keep increasing proportionally with concentration. Table 2 shows: 0.0% → 2, 0.5% → 45 (huge jump), 1.0% → 58 (moderate increase), 1.5% → 60 (small increase of 2), 2.0% → 61 (tiny increase of 1). The change from 60 to 61 indicates plateau (leveling off), not linear growth. At this point, adding more CO₂ barely increases photosynthesis—the plant has reached saturation. Choice C correctly identifies this plateau as evidence against the hypothesis. Choice A misses that overall increase doesn't mean LINEAR increase. Choice B focuses on one pair of trials, missing the plateau at the end. Choice D is factually wrong—rate didn't decrease. Pro tip: "Linear" means proportional increases throughout—plateaus contradict linearity.
Based on Figure 1, which color of light resulted in the lowest rate of photosynthesis, and what is the most likely biological explanation?
Green; chlorophyll reflects green light rather than absorbing it.
Clear; white light contains too much energy for the plant.
Red; red light has the lowest energy.
Blue; chlorophyll absorbs blue light most efficiently.
Explanation
This is a scientific reasoning question requiring both data interpretation and biological knowledge. Figure 1 shows green light produced only 5 bubbles, dramatically lower than clear (45), red (40), and blue (38). This indicates green light is least effective for photosynthesis. The biological explanation is that chlorophyll, the primary photosynthetic pigment, reflects green light (which is why plants appear green to us) rather than absorbing it. Since reflected light isn't absorbed, it can't be used for photosynthesis. Choice C is correct on both parts. Choice A incorrectly identifies blue as lowest (it was 38, not 5). Choice B incorrectly identifies red. Choice D incorrectly identifies clear. Pro tip: Plants appear the color they reflect because they're NOT using that wavelength for photosynthesis.
Ecologists investigated whether adding artificial nest boxes increases the number of breeding pairs of a bird species in urban parks. Four parks received 20 nest boxes each (Box parks) and four similar parks received none (No-box parks). Breeding pairs were counted in spring before installation (Year 0) and the next spring (Year 1). One Box park underwent tree removal between years.
Authors concluded: “Nest boxes caused the population increase observed in Year 1.”
Which of the following is a flaw in the author's reasoning?
They used too many parks; a smaller sample would better isolate the effect of nest boxes.
They fail to measure breeding pairs in Year 0, so no baseline exists for comparison.
They assume causation, but both groups increased; factors like year-to-year conditions could explain the change.
They ignore that tree removal occurred, which must mean nest boxes reduced breeding in all Box parks.
Explanation
The flaw is that the authors assume causation when both groups increased, and other factors like year-to-year environmental conditions could explain the population changes. The data show both No-box parks (12→13 pairs) and Box parks (11→14 pairs) increased from Year 0 to Year 1, indicating favorable breeding conditions affected all parks. While Box parks had a slightly larger increase (3 vs 1 pair), this difference could result from natural population fluctuations, habitat quality differences, or the tree removal mentioned in one Box park. The lack of a true control group receiving no intervention prevents isolating the nest box effect from temporal confounding variables.
Engineers evaluated whether a new tire tread (Tread N) improves braking distance on wet pavement. Ten cars of the same model were tested on a closed track. Each car performed two braking trials from 60 km/h: one with standard tires and one with Tread N. Testing occurred on two different days; Day 2 had heavier rainfall.
The authors concluded: “Tread N reduces wet braking distance under rainy conditions.”
Which statement best evaluates the validity of the author's conclusion?
Invalid: because rainfall differed by day, no comparison between tire types can be made within each day.
Invalid: longer distances on Day 2 prove Tread N increases braking distance in heavy rain.
Valid: Day 2 shows the largest distances, proving tread design is the only factor affecting braking.
Valid: Tread N has shorter mean braking distance than standard tires on both test days.
Explanation
The conclusion is valid because Tread N consistently shows shorter mean braking distances than standard tires on both test days despite different weather conditions. On Day 1 (light rain), Tread N averaged 27.5m versus 29.0m for standard tires, and on Day 2 (heavy rain), it averaged 33.8m versus 34.5m for standard tires. While heavy rain increased stopping distances for both tire types, the consistent pattern across different conditions supports the claim that Tread N improves wet braking performance. The within-day comparisons control for environmental factors like rainfall intensity.
A study examined whether listening to instrumental music improves memory recall. Forty students were assigned to either Music or Silence during a 15-minute study period. Students then completed a 30-word recall test. Researchers also recorded whether students reported being “well-rested” (≥7 hours sleep) or “tired” (<7 hours).
The authors concluded: “Instrumental music significantly improves memory recall for students.”
The conclusion that the authors’ claim is:
Not supported: the data show sleep status has a much larger effect than music, and no significance is demonstrated.
Supported: a 1-word advantage in both groups proves music meaningfully improves recall for all students.
Supported: the difference between well‑rested and tired groups confirms music improves recall by increasing alertness.
Not supported: because tired students score lower, music must decrease recall by distracting them.
Explanation
The claim is not supported because sleep status has a much larger effect on recall than music, and no statistical significance is demonstrated. The data show well-rested students recalled 7-8 more words than tired students (24-25 vs 17-18), while music provided only a 1-word advantage in each sleep group. This 1-word difference is minimal and could easily result from random variation rather than a meaningful effect. The authors cannot conclude 'significant improvement' without statistical testing, and the much larger sleep effect suggests individual factors outweigh any potential music benefit.