GRE Quantitative Quiz: Data Interpretation Graphs

What this quiz covers

This quiz focuses on Data Interpretation Graphs, giving you a quick way to practice the rules, question types, and explanations that matter most for GRE Quantitative.

How to use this quiz

Try each quiz question before looking at the correct answer. Use the explanations to review missed ideas, then come back to similar questions until the pattern feels familiar.

Question 1

1. Wheat, $17{,}600$ (correct answer)
2. Corn, $15{,}000$
3. Soy, $16{,}000$
4. Wheat, $22{,}000$
5. Corn, $25{,}000$

Explanation: This question tests data interpretation skills using a table of harvest amounts and revenue per ton for three crops. The table lists Wheat, Corn, and Soy with tons and USD/ton. To find the highest total revenue, calculate: Wheat 80×220=17,600, Corn 60×250=15,000, Soy 40×400=16,000. Wheat has the highest at 17,600 USD, justifying choice A. A common misread is selecting the highest revenue per ton without multiplying by harvest, leading to Soy and option C. Another error could involve miscalculating Wheat as 80×275 or similar, resulting in 22,000 as in D.

Question 2

1. 38.0
2. 39.6 (correct answer)
3. 41.0
4. 45.0
5. 36.0

Explanation: This question tests data interpretation skills using a table of average weekly hours and number of employees by department. The table lists Sales, Engineering, Support, and HR with hours and employee counts. To find the company-wide average, calculate total hours: 38×25=950, 45×40=1,800, 34×30=1,020, 36×10=360, summing to 4,130, and total employees 105, so 4,130/105 ≈ 39.33 hours. The closest is 39.6, justifying choice B. A common misread is averaging the department averages without weighting, giving (38+45+34+36)/4=38.25, close to 38.0 as in A. Another error could involve miscounting employees, leading to a higher average like 41.0.

Question 3

1. 6
2. 7
3. 8 (correct answer)
4. 9
5. 10

Explanation: This question tests data interpretation skills using a table of daily running distances for a week. The table lists days from Monday to Sunday with kilometers run. To find the median, list the distances: 5, 8, 6, 10, 0, 12, 9, and sort them: 0, 5, 6, 8, 9, 10, 12. For seven values, the median is the fourth, which is 8 km. This justifies choice C as the correct answer. A common misread is calculating the mean instead, giving (5+8+6+10+0+12+9)/7 ≈ 7, leading to option B. Another error could involve not sorting correctly, picking the middle unsorted value like 10 as in E.

Question 4

1. $\frac{31}{115}$ (correct answer)
2. $\frac{31}{42}$
3. $\frac{31}{100}$
4. $\frac{62}{115}$
5. $\frac{31}{57}$

Explanation: This question tests data interpretation skills using a table of annual water use by sector in million gallons. The table lists four sectors: Residential, Commercial, Industrial, and Public services with their respective water usage. To find the fraction for the Commercial sector, first sum the total: 420 + 310 + 270 + 150 = 1,150 million gallons. The Commercial fraction is 310 / 1,150 = 31/115 after simplifying by dividing numerator and denominator by 10. This justifies choice A as the correct answer. A common misread is doubling the Commercial value or confusing it with another sector, leading to 620 / 1,150 = 62/115, which is option D. Another error could involve using an incorrect total like 1,000, resulting in 310/1,000 = 31/100 as in option C.

Question 5

1. $-0.77$ (correct answer)
2. $-0.23$
3. $-1.10$
4. $0.77$
5. $-0.90$

Explanation: This question tests data interpretation skills using a table of chemical concentration over time in minutes. The table lists time points from 0 to 40 minutes with corresponding concentration in mg/L. To find the average rate of change from 10 to 40 minutes, extract the concentrations: 68 mg/L at 10 minutes and 45 mg/L at 40 minutes. The change in concentration is 45 - 68 = -23 mg/L over 40 - 10 = 30 minutes, so the rate is -23 / 30 = -0.7667 ≈ -0.77 mg/L per minute. This justifies choice A as the correct answer. A common misread is using the time from 0 to 40 minutes instead, leading to (45 - 80) / 40 = -0.875 ≈ -0.90, which is option E. Another error might involve forgetting the negative sign for the decrease, resulting in a positive value like option D.

Question 6

1. Monday
2. Tuesday
3. Wednesday (correct answer)
4. Thursday
5. Friday

Explanation: This question tests data interpretation skills using a table of packages delivered and fuel used for each day of the week. The table provides two columns for each day: the number of packages delivered and the gallons of fuel used. To determine the day with the greatest fuel efficiency, calculate the packages per gallon by dividing the number of packages by the fuel used for each day. The calculations yield: Monday 480/32 = 15, Tuesday 520/35 ≈ 14.86, Wednesday 500/30 ≈ 16.67, Thursday 560/40 = 14, and Friday 540/36 = 15. Wednesday has the highest efficiency at approximately 16.67 packages per gallon, justifying choice C as the correct answer. A common misread is selecting the day with the most packages delivered without dividing by fuel, which might lead to choosing Thursday. Another error could involve inverting the ratio to gallons per package, resulting in an incorrect lowest value for Wednesday instead.

Question 7

1. Trip 1
2. Trip 2
3. Trip 3
4. Trip 4 (correct answer)
5. Trip 5

Explanation: This question tests data interpretation skills using a table of distance and time for five trips. The table lists miles and minutes for each trip. To find the lowest average speed in mph, convert minutes to hours and calculate speed: Trip 1: 12 / (24/60) = 30 mph, Trip 2: 15 / (30/60) = 30 mph, Trip 3: 10 / (20/60) = 30 mph, Trip 4: 18 / (45/60) = 24 mph, Trip 5: 20 / (40/60) = 30 mph. Trip 4 has the lowest speed at 24 mph, justifying choice D. A common misread is forgetting to convert minutes to hours, leading to speeds in miles per minute and incorrectly selecting Trip 4 still, but miscomparing. Another error could involve calculating time per mile instead, inverting the values and picking Trip 4 incorrectly as highest.

Question 8

1. The balance increased every month.
2. The largest month-to-month decrease occurred from February to March. (correct answer)
3. The balance decreased from March to April.
4. The balance in May was less than in February.
5. The smallest month-to-month increase occurred from January to February.

Explanation: This question tests data interpretation skills using a table of end-of-month savings balances from January to May. The table lists months with USD balances. To evaluate statements, examine changes: Jan to Feb +150, Feb to Mar -70, Mar to Apr +180, Apr to May +140. The largest decrease is Feb to Mar at -70, supporting statement B. Other statements like A (increased every month) fail due to the decrease. A common misread is overlooking the decrease, leading to A. Another error could involve comparing absolute balances, incorrectly supporting D when May is higher than February.

Question 9

1. $12.5\%$
2. $15.0\%$
3. $18.8\%$ (correct answer)
4. $9.0\%$
5. $2.0\%$

Explanation: This question tests data interpretation skills using a table of stock closing prices over five days. The table lists days 1 to 5 with USD prices. To find the percent increase from Day 1 to Day 5, calculate (57 - 48)/48 × 100% = 9/48 ≈ 18.75%. The closest is 18.8%, justifying choice C. A common misread is using Day 2 or another as the base, like from 51 to 57 = about 11.8%, not matching options directly. Another error could involve absolute increase divided by average, approximating 15% as in B.

Question 10

1. Group A
2. Group B
3. Group C
4. Group D
5. Groups A and C are tied for highest (correct answer)

Explanation: This question tests data interpretation skills using a table of invited and completed surveys by group. The table lists four groups with invited and completed numbers. To find the highest completion rate, calculate rates: Group A 90/120 = 0.75, B 105/150 = 0.70, C 60/80 = 0.75, D 140/200 = 0.70. Groups A and C tie at 75%, justifying choice E. A common misread is comparing completed numbers without dividing by invited, leading to Group D with 140 as highest. Another error could involve miscalculating one rate, such as 90/120 as 0.70, incorrectly picking Group C alone.

Question 11

1. North
2. South
3. East (correct answer)
4. West
5. North and South are tied for highest

Explanation: This question tests data interpretation skills using a table of total and late deliveries by region. The table lists North, South, East, West with delivery counts. To find the highest late rate, calculate: North 36/1,200=0.03, South 27/900=0.03, East 60/1,500=0.04, West 16/800=0.02. East has the highest at 4%, justifying choice C. A common misread is comparing late deliveries without dividing by total, leading to East still but missing ties. Another error could involve tying North and South as highest while ignoring East's higher rate, as in option E.

Question 12

1. Chess
2. Debate
3. Robotics (correct answer)
4. All three clubs had the same percentage increase
5. Cannot be determined from the table

Explanation: This question tests data interpretation skills using a table of club enrollment over three years. The table lists Chess, Debate, and Robotics with student counts for 2022, 2023, and 2024. To find the greatest percentage increase from 2022 to 2024, calculate: Chess (50 - 40)/40 = 25%, Debate (60 - 55)/55 ≈ 9.09%, Robotics (45 - 30)/30 = 50%. Robotics has the greatest at 50%, justifying choice C. A common misread is using 2023 instead of 2024, leading to Robotics' 20% and incorrectly picking Chess at 15%. Another error could involve absolute increases, picking Robotics' 15 but missing Debate's smaller base.

Question 13

1. M1
2. M2
3. M3 (correct answer)
4. M1 and M3 are tied
5. M2 and M3 are tied

Explanation: This question tests data interpretation skills using a table of energy used and output for three machines. The table lists M1, M2, M3 with kWh and units. To find the lowest energy per unit, calculate: M1 120/300=0.4, M2 150/330≈0.455, M3 90/240=0.375. M3 has the lowest at 0.375, justifying choice C. A common misread is calculating units per kWh instead, leading to M3's 2.667 and incorrectly picking highest efficiency as lowest energy use. Another error could involve tying M1 and M3 if miscalculating M3 as 0.4.