FREE SAT Command of Evidence (Quantitative) Questions and Answers 3

Question 1

A researcher is analyzing the relationship between the percentage of a country's GDP spent on research and development (R&D) and the number of patent applications filed per million people. The researcher posits that while increased R&D spending is generally associated with more innovation, the efficiency of this spending can vary, suggesting that a higher percentage of R&D spending does not guarantee a proportionally higher rate of patent applications.

**R&D Spending vs. Patent Applications (2023)**

| Country | R&D Spending (% of GDP) | Patent Applications (per million people) |
|---|---|---|
| Country A | 1.8% | 150 |
| Country B | 2.5% | 300 |
| Country C | 2.4% | 310 |
| Country D | 3.2% | 350 |
| Country E | 3.1% | 345 |

Which choice most effectively uses data from the table to illustrate the researcher's claim about the variable efficiency of R&D spending?

Accepted Answer

Country B and Country C had similar R&D spending percentages (2.5% and 2.4%, respectively), but Country C had a slightly higher number of patent applications per million people.

Answer

Country D had the highest R&D spending at 3.2% and also had the highest number of patent applications at 350 per million people.

Answer

Country A had the lowest R&D spending at 1.8% and the lowest number of patent applications at 150.

Answer

The difference in patent applications between Country E (345) and Country D (350) is minimal compared to their difference in R&D spending.

Question 2

A climatologist studied the effect of rising sea surface temperatures (SST) on the average wind speed of hurricanes in two different ocean basins, the Atlantic and the Pacific. The climatologist hypothesized that the impact of SST increases would be more pronounced in the Atlantic basin due to other atmospheric factors. The data below shows the change in average wind speed for every 1°C increase in SST over two decades.

**Change in Average Hurricane Wind Speed per 1°C SST Increase**

| Decade | Atlantic Basin (km/h increase) | Pacific Basin (km/h increase) |
|---|---|---|
| 2000-2009 | +5.2 | +4.8 |
| 2010-2019 | +6.5 | +5.1 |

Which choice most effectively uses data from the table to support the climatologist's hypothesis?

Accepted Answer

In both decades, the increase in wind speed per 1°C SST increase was greater in the Atlantic basin than in the Pacific basin.

Answer

In the 2000-2009 decade, the increase in wind speed in the Atlantic basin was 5.2 km/h, while in the Pacific basin it was 4.8 km/h.

Answer

The increase in wind speed in the Pacific basin was greater in the 2010-2019 decade (+5.1 km/h) than it was in the 2000-2009 decade (+4.8 km/h).

Answer

The total increase in wind speed across both decades was 11.7 km/h in the Atlantic and 9.9 km/h in the Pacific.

Question 3

A study investigated the efficacy of two different water purification tablets, 'Aqua-Clear' and 'Pristine-H2O', by measuring the percentage reduction of two common bacteria, E. coli and Giardia, after 30 minutes. The study's authors aimed to show that while both are effective, their performance profiles differ.

**Bacterial Reduction (%) after 30 Minutes**

| Tablet | E. coli Reduction | Giardia Reduction |
|---|---|---|
| Aqua-Clear | 99.9% | 98.5% |
| Pristine-H2O | 99.2% | 99.8% |

Which choice most effectively uses data from the table to complete the claim that the tablets' performance profiles differ significantly?

Accepted Answer

Aqua-Clear was more effective against E. coli, whereas Pristine-H2O was more effective against Giardia.

Answer

Both tablets achieved over a 99% reduction in E. coli, with Aqua-Clear performing slightly better at 99.9% compared to Pristine-H2O's 99.2%.

Answer

Pristine-H2O was more effective at reducing Giardia, achieving a 99.8% reduction, while Aqua-Clear achieved a 98.5% reduction.

Answer

The average reduction rate for Aqua-Clear across both bacteria was 99.2%, while for Pristine-H2O it was 99.5%.

Question 4

An economist argues that in a specific developing nation, the official unemployment rate does not fully capture the extent of underemployment. To support this, she presents data comparing the official unemployment rate with the percentage of the workforce that is employed part-time but seeking full-time work (PT-SFT).

**Labor Statistics for a Developing Nation (2020-2023)**

| Year | Official Unemployment Rate | PT-SFT Workforce Percentage |
|---|---|---|
| 2020 | 5.5% | 8.0% |
| 2021 | 5.2% | 8.5% |
| 2022 | 4.9% | 8.3% |
| 2023 | 4.8% | 8.9% |

Which choice most effectively uses data from the table to support the economist's argument?

Accepted Answer

In 2023, the official unemployment rate reached its lowest point of 4.8%, while the percentage of the PT-SFT workforce was at its highest point of 8.9%.

Answer

The official unemployment rate showed a steady decline from 5.5% in 2020 to 4.8% in 2023.

Answer

The PT-SFT workforce percentage fluctuated, starting at 8.0% in 2020 and ending at 8.9% in 2023.

Answer

In every year shown, the percentage of the PT-SFT workforce was significantly higher than the official unemployment rate.

Question 5

A materials scientist is developing a new polymer blend and tests its performance at different temperatures. The scientist claims that the material's tensile strength decreases non-linearly as temperature increases, with the most significant drop occurring between 50°C and 75°C.

**Tensile Strength of Polymer Blend**

| Temperature (°C) | Tensile Strength (MPa) |
|---|---|
| 25 | 120 |
| 50 | 115 |
| 75 | 95 |
| 100 | 85 |

Which choice most effectively uses data from the table to support the scientist's claim?

Accepted Answer

The tensile strength decreased by only 5 MPa between 25°C and 50°C, but it decreased by 20 MPa between 50°C and 75°C.

Answer

The tensile strength at 25°C was 120 MPa, which was the highest recorded strength.

Answer

The decrease in tensile strength between 75°C and 100°C was 10 MPa.

Answer

Overall, the tensile strength decreased from 120 MPa at 25°C to 85 MPa at 100°C.

Question 6

A city's transportation department analyzed commute times for residents using public transit versus personal vehicles. They hypothesized that while public transit might have a longer average commute time, its commute times are more consistent and less affected by peak traffic hours.

**Average Commute Time and Variability (in minutes)**

| Mode of Transport | Average Commute | Standard Deviation* |
|---|---|---|
| Personal Vehicle | 35 | 12.5 |
| Public Transit | 45 | 4.5 |

*Standard Deviation is a measure of variability; a lower number means more consistency.

Which choice most effectively uses the data to support the department's full hypothesis?

Accepted Answer

While the average commute time for public transit is 10 minutes longer than for a personal vehicle, its standard deviation is nearly three times lower.

Answer

The average commute time for public transit is 45 minutes, which is 10 minutes longer than the average for a personal vehicle.

Answer

The standard deviation for public transit commute times is 4.5, whereas for personal vehicles it is 12.5.

Answer

The difference in the average commute times between the two modes of transport is 10 minutes.