Command of Evidence (Quantitative) Flashcards

A nutrition researcher claims: 'Among adults aged 18–35, protein intake from plant sources has become the primary driver of total protein consumption.' The table below shows average daily protein intake (in grams) for this age group in 2023. | Source | Avg. Daily Intake (g) | |---|---| | Meat/poultry | 48 | | Dairy | 22 | | Plant-based | 31 | | Seafood | 14 | | Other | 5 | Which choice most accurately uses the data to evaluate the researcher's claim?

Answer: The claim is unsupported because meat/poultry intake (48g) is the single largest source, exceeding plant-based intake (31g) by 17 grams.

The researcher asserts plant-based protein is the 'primary driver,' meaning the largest single source. The table directly contradicts this: meat/poultry at 48g is the largest source, exceeding plant-based at 31g. Choice A is true but irrelevant to 'primary driver' status. Choice B is accurate math but second-highest share still doesn't make it the primary driver. Choice D is numerically true (36g > 31g) but arbitrarily combines two unrelated sources to beat one — that logic doesn't establish which single source dominates.

A sociologist concludes: 'In Greenfield County, the relationship between education level and median annual income is consistently positive — each additional level of education corresponds to higher income.' The table shows 2024 data. | Education Level | Median Annual Income | |---|---| | Less than high school | $28,400 | | High school diploma | $36,700 | | Some college, no degree | $39,200 | | Associate degree | $43,800 | | Bachelor's degree | $61,500 | | Graduate degree | $58,900 | Which finding from the table most directly undermines the sociologist's conclusion?

Answer: Graduate degree holders report a median income of $58,900 — lower than bachelor's degree holders at $61,500 — breaking the pattern of income rising with each successive education level.

The sociologist claims income rises with each additional education level — a 'consistently positive' step-by-step relationship. The only direct falsification in the data is that graduate degree holders ($58,900) actually earn less than bachelor's degree holders ($61,500). This single reversal is enough to disprove 'consistently positive.' Choices A, B, and D all point to uneven or non-linear gains, but unevenness is compatible with a consistently positive relationship — none of them show a decrease, which is what 'consistently positive' rules out.

A city planner argues: 'The data show that increasing the number of bus routes in a neighborhood directly causes a reduction in car ownership rates.' A scatterplot of 14 neighborhoods displays bus routes (x-axis) vs. car ownership rate (y-axis), with a negative line of best fit (r = −0.71). However, three high-income neighborhoods each have 8–10 bus routes and car ownership rates above 85%. Which of the following most accurately identifies a limitation of the planner's conclusion?

Answer: The three high-income neighborhoods with many bus routes but high car ownership suggest that income may be a confounding variable, making it impossible to attribute the overall pattern to bus routes alone.

The planner's critical error is claiming direct causation. Choice D directly challenges this by identifying a confounding variable: high-income neighborhoods have abundant bus routes yet high car ownership — the opposite of the claimed effect. This implies that wealth (not bus route count) may be the underlying driver of both variables. Choice A is incorrect; r = −0.71 is a moderately strong correlation. Choice B is methodologically improper and would cherry-pick data. Choice C raises a valid measurement concern but does not use the quantitative data from the scatterplot to challenge the specific causal claim.

A pharmacologist claims 'Drug B is the superior treatment option based on these trial results.' A colleague disputes this. The table shows results from a 12-week clinical trial (n = 200 per group). | Metric | Drug A | Drug B | |---|---|---| | Response rate (≥10 mmHg reduction) | 68% | 74% | | Serious adverse events | 12 | 7 | | Mean systolic BP reduction (mmHg) | 14.2 | 12.8 | Which choice best supports the colleague's position that the data do not clearly establish Drug B as superior?

Answer: Drug A produced a greater mean blood pressure reduction (14.2 mmHg vs. 12.8 mmHg), meaning Drug A outperforms Drug B on a continuous efficacy measure even though its binary response rate is lower.

The pharmacologist points to Drug B's higher response rate (74% vs. 68%) and fewer adverse events. But Drug A achieved a greater mean BP reduction (14.2 vs. 12.8 mmHg) — meaning that on the continuous scale of how much blood pressure actually fell, Drug A is more effective. This genuine trade-off (Drug B wins on response rate and safety; Drug A wins on magnitude of reduction) is exactly what the colleague needs to argue the data are ambiguous. Choice A raises a fair point but doesn't use a competing data metric. Choice B actively supports Drug B, undermining the colleague. Choice C is irrelevant to comparative superiority.

A company report states: 'Employee satisfaction has been on a consistent upward trajectory company-wide over the three-year period.' The table shows the percentage of employees reporting high job satisfaction by department. | Department | 2021 | 2022 | 2023 | |---|---|---|---| | Engineering | 72% | 68% | 74% | | Marketing | 65% | 71% | 69% | | Sales | 58% | 55% | 52% | | Operations | 61% | 63% | 70% | Which choice best explains why the company's claim is not fully supported by the data?

Answer: Sales satisfaction fell in each of the three years (58% → 55% → 52%), and Marketing's satisfaction declined from 2022 to 2023, contradicting the claim of a consistent company-wide upward trajectory.

The claim requires a 'consistent upward trajectory company-wide' — meaning every department should be trending up. Sales declined every single year (58→55→52), a clear counter-example. Marketing also fell from its 2022 peak (71%) back to 69% in 2023. These two departments directly falsify 'consistent upward trajectory company-wide.' Choice A is true of Engineering, but Engineering's 3-year net trend is still positive (72→74), so this is a temporary dip, not a refutation of the trend. Choice C makes a statistical inference not directly readable from the table. Choice D is a methodological concern, not a data-based challenge.

A researcher concludes: 'Video lecture completion is the most reliable predictor of final exam performance in this online course.' The table shows data from 240 students. | Video Completion Rate | Avg. Final Exam Score | Avg. Practice Sets Completed (out of 10) | |---|---|---| | 75% | 82.1 | 8.4 | Which of the following most directly challenges the researcher's claim that video completion is the 'most reliable predictor'?

Answer: Students in the >75% video completion group also completed far more practice sets (8.4/10) than those in the <25% group (3.1/10), making it impossible to isolate video completion as the primary driver of higher scores.

The researcher's specific claim is that video completion is the 'most reliable predictor' — implying it's the dominant variable. But the table reveals that practice set completion rises in lockstep with video completion (3.1→4.7→6.2→8.4). Since both variables increase together, the data cannot isolate which one actually drives exam scores. This is a classic confounding problem: the researcher cannot establish video completion as the primary cause when another plausible predictor moves identically. Choice A notes non-linearity but doesn't challenge which variable is the predictor. Choice C is accurate but vague. Choice D raises a sample concern but doesn't use the table's quantitative data.