data-interpretation-s01-q01
Locate the day you are asked about before reading any number. The Wednesday entry is 51 loans.
This is untimed educational practice for one cognitive skill. It is not a clinical, diagnostic, employment, or professionally recognized assessment, and it does not produce an IQ score or credential.
Locate the day you are asked about before reading any number. The Wednesday entry is 51 loans.
Scan the whole column for the smallest value rather than stopping at the first low number. July's 20 mm is the minimum.
Pick out only the two rows the question names, then subtract: £42 − £19 = £23.
Add every row, checking you have not skipped the smallest one: 120 + 35 + 18 + 9 = 182.
Compare all four periods individually rather than by day: Saturday afternoon's 340 is the highest single figure.
Count every row that matches the exact value asked for. Year 8 and Year 10 both show 9, giving two groups.
Check the gap between each neighbouring pair: 08:10 to 08:35 is 25 minutes, and the same gap repeats down the column.
Read the quantity for every item before deciding: rulers, at 95, sit below all the others.
Sum the three rows carefully: 58 + 84 + 27 = 169 cups.
Match the label first, then the value. The Week 2 row reads 81 parcels, even though nearby weeks share similar figures.
Take the two named bars and subtract the smaller from the larger: 45 − 20 = 25 units.
Test each pairing against the target sum: 112 + 98 = 210, while the other pairings give 176, 144 and 110.
First rank the days to find the top two (Sunday 105 and Wednesday 92), then add them: 105 + 92 = 197.
A 'times as many' comparison is a division, not a subtraction: 120 ÷ 30 = 4.
The gap to close is the difference between the bars: 340 − 290 = 50 units.
Check each figure against the threshold, taking care with near-misses: only mint, at 38, falls below 40.
Add all four bars, pairing numbers that make round sums to reduce slips: (28 + 22) + (34 + 36) = 50 + 70 = 120.
Identify the extremes first (paper 340 kg and metal 95 kg), then subtract: 340 − 95 = 245 kg.
Work out the target value first (180 + 60 = 240), then find which bar matches it, Q4.
Compute each candidate difference rather than estimating: 420 − 385 = 35, while the other pairings give 75, 15 and 125.
Divide the part by the whole and multiply by 100: 90 ÷ 200 = 0.45, which is 45%.
The question asks for the survivors, so use the remaining 80%: 0.80 × 250 = 200.
Write the part over the whole and simplify: 60/240 reduces to 1/4.
Total the votes first (10,000), then divide: 4,500 ÷ 10,000 = 45%. A percentage always needs the full total as its base.
Category percentages of one whole must sum to 100, so the walkers make up 100 − (35 + 25 + 30) = 10%.
Convert the percentage to a decimal and multiply: 0.40 × 320 = 128.
Divide the late orders by the total: 45 ÷ 150 = 0.30, so 30%, the raw count of 45 is not itself the percentage.
Scale the ratio to the actual total: 96 ÷ 8 = 12 groups of eight, and 12 × 3 = 36 pupils.
Apply the ticket-sales share to the total: 0.30 × £600,000 = £180,000.
Here the part is known and the whole is missing, so divide by the percentage: 5,200 ÷ 0.40 = 13,000 visitors.
Work out each month-on-month change (+1,000; +2,000; −1,000; +3,000): the biggest increase, +3,000, is from April to May.
A peak is the highest point before the series turns downward: 16°C at 15:00, after which the reading falls.
Compare each day with its predecessor: Tuesday and Wednesday rose, Thursday fell, so the level rose on two days.
The series climbs by a constant 300 each year, so extending the pattern gives 2,100 + 300 = 2,400.
The fall is a constant 80 per week, so week 4 is projected at 480 − 80 = 400.
Measure the size of each change regardless of direction: +£3,000 into Q2, −£6,000 into Q3, and +£9,000 into Q4, the largest.
Between day 1 and day 5 there are four daily steps, not five, so divide the total fall by 4: (900 − 660) ÷ 4 = 60 litres.
A doubling pattern is multiplicative, not additive: 2,000 × 2 = 4,000 for June.
An isolated sharp drop that largely reverses the following year is the signature of an outlier caused by a one-off event, not a genuine trend change.
The rise is 160 cars over 4 hours, or 40 per hour; two hours in, occupancy is 40 + (2 × 40) = 120.
Total the scores and divide by how many there are: 330 ÷ 5 = 66.
Add the four values (184) and divide by 4 to get 46 deliveries per day.
Scale the rate to the time asked for: 30 minutes is half an hour, so an hour yields 240 × 2 = 480 bottles.
Sort the values first (7, 12, 14, 18, 25); the median is the middle entry of the sorted list, 14.
Average speed is distance divided by time: 84 ÷ 3.5 = 24 km/h.
A mean can be reversed into a total by multiplying by the number of periods: 40 × 7 = 280 calls.
Rebuild the total from the mean (22 × 4 = 88 mm), then subtract the known weeks: 88 − 63 = 25 mm.
The mode is the most frequent value: size 8 appears three times, more than any other.
Divide the job size by the rate: 630 ÷ 45 = 14 minutes.
Weight each rate by how many staff earn it: (3 × £12 + 1 × £16) ÷ 4 = £52 ÷ 4 = £13, not the midpoint of the two rates.
Apply the slice's percentage to the whole: 0.15 × £2,000 = £300.
A full circle is 360°, so divide the angle by 360: 90 ÷ 360 = 1/4, which is 25%.
The segment is 120/360 = one third of the circle, and one third of 360 members is 120.
Slices of one pie must total 100%, so x = 100 − (40 + 35 + 5) = 20.
Driving takes 40 and cycling 20, leaving 20 employees; split equally, walking accounts for 10 of them.
Percentages from different-sized wholes cannot be compared directly. Convert each to an amount first: £27,000 − £12,000 = £15,000.
Multiply the share by the total number of votes: 0.40 × 1,200 = 480.
Convert the angle to a fraction of the circle (45/360 = 1/8), then take that fraction of the total: 720 ÷ 8 = 90.
Add each candidate pair of shares and look for 50%: cake plus fruit gives 30 + 20 = 50%.
Apply the percentage to the amount raised: 0.09 × £150,000 = £13,500. A 9% share is not the same as £9,000.
Cost each line separately, then add: (3 × £2.40) + (2 × £1.10) = £7.20 + £2.20 = £9.40, ignoring the folder entirely.
Classify each night against the table's bands before pricing it: £85 + £110 + £110 = £305.
Work out each pay component at its own rate: 38 × £11 = £418, and overtime at £16.50 gives 4 × £16.50 = £66, totalling £484.
Apply each movement with the correct sign: 500 + 240 − 380 + 15 = 375. Returns come back into stock, so they are added.
Calculate the two parts separately and convert pence to pounds: £8.40 standing charge + £50.40 usage = £58.80.
Apply the discount only where the table allows it: adults cost £29.00 × 0.75 = £21.75, children £14.50, giving £36.25.
Convert first, then subtract in the same currency: £400 × 1.15 = €460, and €460 − €322 = €138.
Multiply each line's rate by its own running time before adding: (60 × 6) + (45 × 8) = 360 + 360 = 720 units.
Price the items separately (£8.95 + £3.05 + £1.80 = £13.80), then subtract the deal price: £13.80 − £12.50 = £1.30.
Combine the fixed and variable charges: (2 × £45) + (250 × £0.22) = £90 + £55 = £145.
Divide the change by the original value: £18,000 ÷ £180,000 = 0.10, a 10% increase.
The fall of 3,750 is measured against the starting figure: 3,750 ÷ 25,000 = 15%.
An index of 130 against a base of 100 means multiplying by 1.30: £46 × 1.30 = £59.80.
Equal percentage rises and falls do not cancel because they act on different bases: 1.20 × 0.80 = 0.96, which is 4% below the start.
Use the original figure as the base, not the new one: 2,000 ÷ 8,000 = 25%.
The sale price is 70% of the original, so divide rather than add 30% back on: £42 ÷ 0.70 = £60.
Between two index readings, the base is the earlier reading, not 100: (121 − 110) ÷ 110 = 10%.
The growth of 16,000 is divided by the starting population: 16,000 ÷ 64,000 = 25%.
This year is 120% of last year, so divide by 1.20: £2.4m ÷ 1.2 = £2.0m, subtracting 20% of £2.4m would use the wrong base.
A 12% fall leaves 88% of the original: 4,500 × 0.88 = 3,960 kWh.
Multiply each day's visitors by its own rate before comparing: Monday 400 × 10% = 40 and Tuesday 500 × 8% = 40, the same.
Revenue joins the two sources by multiplication: 240 units × £12.50 = £3,000.
Raw membership counts mislead when populations differ: compute each rate: North 2,500/50,000 = 5% beats South's 3,200/80,000 = 4%.
Chain the times step by step: 10:40 + 1:35 = 12:15 arrival, and adding the 20-minute wait gives 12:35.
Combine the capacity first (2 × 30 = 60 hours per week), then divide the workload: 180 ÷ 60 = 3 weeks.
Apply the unsold rate from one chart to the volume from the other: 95% of 320 = 304 loaves sold.
Take 15% of the reference price and subtract it: £600 − £90 = £510.
Multiply each result count by its points value and sum: (6 × 3) + (2 × 1) + (2 × 0) = 20 points.
The irrigation requirement is the gap between need and supply: 90 − 60 = 30 mm.
Convert each percentage to a count before adding, 580 + 310 = 890, because percentages from different sample sizes cannot be added directly.
The table establishes only that the two series moved oppositely; causation, forecasts, and per-employee productivity all require information the table does not contain.
Only the direct restatement of a figure is safe: doubling means injuries rose. Linking the two statistics causally, or inferring who was injured, goes beyond the chart.
The problem is selection bias: people sampled at a gym are far more likely to exercise than the general adult population, whatever the sample size.
With unequal group sizes, compare rates, not raw counts: 60/400 = 15% against 10/100 = 10%. The sixfold count difference mostly reflects the fourfold group-size difference.
An average summarises the whole distribution: some prices may have fallen while larger rises elsewhere pulled the mean up, so no claim about every house follows.
When two series move together, consider a common cause before assuming one drives the other, hot weather plausibly increases both swimming and ice-cream sales.
A truncated axis exaggerates small gaps, so read the actual values instead of the bar heights: 98 versus 94 is a difference of only four points.
An overall rate must weight each group by its size: (18,200 + 1,900) ÷ 22,000 ≈ 91.4%. Averaging the two percentages ignores that weekday services outnumber weekend ones tenfold.
Observational data shows association only: either variable could influence the other, or something else could influence both, so only the association itself is a safe conclusion.
Without a controlled comparison, only the descriptive before-and-after change is defensible; causes, preferences, and forecasts would each need evidence the dashboard does not provide.