10 original Command of Evidence: Quantitative questions, easiest first. Read a table or graph and pick the choice the data actually supports. Answer them all, then submit once to see every answer explained.
A retailer tracked customer return requests before and after redesigning its online size guide:
| Month 1 (before change) | 640 returns |
|---|---|
| Month 2 (before change) | 615 returns |
| Month 3 (after change) | 390 returns |
| Month 4 (after change) | 355 returns |
A customer service manager claims the redesigned size guide caused a decrease in returns.
Does the data support the manager's claim?
A — Yes, because returns were notably lower in the two months after the change than in the two months before it.. Returns fell from roughly 615–640 to roughly 355–390 after the change, a clear and notable decrease consistent with the claim. The data covers four months, so choice D is factually wrong, and choice B misreads the direction of change.
A meal-kit company tracked the percentage of subscribers who renewed their monthly subscription, broken down by how many meal-kit deliveries they had used in their first three months:
| 1–3 deliveries | 19% renewed |
|---|---|
| 4–6 deliveries | 47% renewed |
| 7–9 deliveries | 66% renewed |
| 10+ deliveries | 79% renewed |
Which choice best describes the relationship shown in the table?
D — Renewal rate generally increases as the number of deliveries used increases.. The renewal percentages rise steadily (19%→47%→66%→79%) as delivery count increases, showing a clear positive relationship, matching choice D.
A researcher recorded average monthly temperature and the number of reported pipe-burst repair calls in a city across four months:
| November | 42°F, 11 calls |
|---|---|
| December | 28°F, 34 calls |
| January | 19°F, 58 calls |
| February | 24°F, 45 calls |
A plumbing company claims that repair calls are strongly associated with temperature, with lower temperatures linked to more calls.
Does the data support the plumbing company's claim?
A — Yes, because months with lower temperatures generally also had more repair calls.. As temperature falls from November (42°F) to January (19°F), calls rise (11→34→58), showing a consistent inverse association, supporting the claim. Choice C misstates January as having the highest temperature when it had the lowest.
A researcher recorded average weekly rainfall and the number of reported storm drain clogs in a city across four weeks:
| Week 1 | 0.4 in. rain, 8 clogs |
|---|---|
| Week 2 | 1.6 in. rain, 22 clogs |
| Week 3 | 2.9 in. rain, 41 clogs |
| Week 4 | 0.2 in. rain, 5 clogs |
A public works official claims that storm drain clogs are strongly associated with rainfall, with more rainfall linked to more clogs.
Does the data support the official's claim?
D — Yes, because weeks with more rainfall generally also had more clogs.. As rainfall rises from Week 4 (0.2 in.) to Week 3 (2.9 in.), clogs also rise (5→8→22→41 following the rainfall pattern), showing a consistent positive association, supporting the claim. Choice B misstates Week 4 as having the highest rainfall when it had the lowest.
A study tracked the percentage of survey respondents who reported regularly using a public library, broken down by distance from the nearest branch:
| Under 0.5 mi | 52% |
|---|---|
| 0.5–1 mi | 38% |
| 1–2 mi | 33% |
| Over 2 mi | 41% |
A columnist claims that the data show library use decreases steadily as distance from a branch increases.
Does the table support the columnist's claim?
D — No, because the percentage does not decrease steadily; it drops through the first three groups but then rises for the farthest group.. The percentages go 52% → 38% → 33% → 41%, which drops for three groups then rises for the farthest—not a steady decrease. Choice D correctly identifies this non-monotonic pattern; choice C misreads which group has the lowest value (1–2 mi is lowest, not over 2 mi).
A city compared the number of potholes repaired per month before and after switching to a new road-maintenance scheduling system:
| 3 months before switch | 52, 48, 55 repairs |
|---|---|
| 3 months after switch | 89, 94, 86 repairs |
A city official claims that the new scheduling system roughly doubled the monthly repair rate.
Does the data support the official's claim?
C — Yes, because the average monthly repairs after the switch (about 90) is roughly double the average before the switch (about 52).. The average before (52+48+55)/3 ≈ 52 and after (89+94+86)/3 ≈ 90, which is roughly, though not exactly, double—supporting the official's claim as a reasonable approximation.
A field study measured the number of butterfly sightings per hour in three meadow plots with different levels of mowing frequency:
| No mowing | 38 sightings/hour |
|---|---|
| Occasional mowing | 24 sightings/hour |
| Frequent mowing | 9 sightings/hour |
An ecologist claims that as mowing frequency increases, butterfly sightings decrease.
Does the table support the ecologist's claim?
B — Yes, because sighting counts decrease consistently as mowing frequency increases from none to occasional to frequent.. The values 38 → 24 → 9 decrease consistently as mowing frequency rises from none to occasional to frequent, directly supporting the claim of an inverse relationship. Choice A misreads the data—frequent mowing had fewer, not more, sightings.
A researcher tracked the number of craft vendors and average weekly vendor revenue across five market events:
| Event A | 10 vendors, $340 avg. revenue |
|---|---|
| Event B | 18 vendors, $510 avg. revenue |
| Event C | 25 vendors, $470 avg. revenue |
| Event D | 33 vendors, $600 avg. revenue |
| Event E | 14 vendors, $310 avg. revenue |
Which choice best describes the relationship shown in the table?
A — Events with more vendors did not always have higher average vendor revenue than events with fewer vendors.. Event C had more vendors (25) than Event B (18) but lower average revenue ($470 vs. $510), showing the relationship is not perfectly consistent—matching choice A, not the absolute claim in choice D.
A researcher measured average productivity scores for employees who reported different amounts of natural light exposure in their workspace:
| Minimal light | 61 points |
|---|---|
| Some light | 70 points |
| Ample light | 84 points |
| Excessive light | 75 points |
A workplace consultant claims that productivity increases continuously the more natural light an employee receives.
Does the data support the consultant's claim?
A — No, because scores rise from minimal to ample light, but then fall for employees with excessive light.. Scores rise from 61 to 70 to 84, but then drop to 75 for the excessive-light group—not a continuous increase. Choice A correctly identifies this non-monotonic pattern, disproving the 'continuously' claim, even though choice C is technically true in isolation.
A language-learning app tracked the percentage of users who reached conversational fluency, broken down by how many minutes per day they practiced:
| Under 10 min/day | 8% reached fluency |
|---|---|
| 10–20 min/day | 22% reached fluency |
| 20–40 min/day | 41% reached fluency |
| Over 40 min/day | 53% reached fluency |
Which choice best describes the relationship shown in the table?
D — The percentage reaching fluency generally increases as daily practice time increases.. The fluency percentages rise steadily (8%→22%→41%→53%) as practice time increases, showing a clear positive relationship, matching choice D.
Score:
Every question above is now marked up: the correct answer is highlighted, any wrong option you picked is flagged, and each explanation is open.
No. Every question here is original, written to the College Board's published Digital SAT Reading & Writing specification for the Command of Evidence: Quantitative skill. No retired or copyrighted College Board material appears anywhere on this site.
Command of Evidence (Quantitative) pairs a short passage with a table or graph and asks which choice most effectively uses that data to complete or support a stated claim. No arithmetic beyond comparison is required — it is a reading question about a data display, not a maths question.
Read the title, the axis labels, the units and the column headers before you read a single answer choice; most wrong answers survive only because the reader assumed what the numbers measured. Then find the specific comparison the claim needs, locate exactly those cells or points, and check each choice against them.
No, and deliberately so. This drill is 10 Command of Evidence: Quantitative questions back to back; a real Reading & Writing module is 27 questions in 32 minutes drawn from all eleven skills. Use a drill to fix one weakness, then take a full module to practice the real thing.
No. The SAT has no penalty for a wrong answer — a blank and a wrong guess both score zero — so answer every question, including the ones you have to guess.