Digital SAT · Math

Statistics & Data Distribution on the Digital SAT: All Question Types

Statistics and Data Distribution covers reading and reasoning about data: measures of center and spread, interpreting a line of best fit, and drawing valid conclusions from a sample with a margin of error. Some questions compute a mean or compare a mean to a median across a distribution; others are reasoning questions with nothing to calculate, where random sampling sets what population you can generalize to and a larger sample shrinks the margin of error. This is a Problem-Solving and Data Analysis skill. The interpretation questions reward careful reading over arithmetic, and the frequent traps are overstating a sample's reach and getting the margin of error backward, thinking a bigger sample widens it rather than tightening it.

College Board skill: Problem-Solving and Data Analysis: Data distributions and sample statistics

How Statistics & Data Distribution is tested

how often it appears
~3 per test
how often it appears
typical difficulty
Mostly easy
typical difficulty
practice questions in our bank
234
practice questions in our bank
A few per test, usually on the easier end, spanning mean and median, line of best fit, and sampling with a margin of error. Some items compute a value and others are pure reasoning with nothing to calculate. The reasoning ones carry the traps: overstating what a sample supports, or getting the margin of error backward by thinking a bigger sample widens it. Read how the sample was drawn and what the interval claims.
The move it rewards

Pick the right measure

Match the question to the right statistic: mean/median for center, range/SD for spread. Outliers pull the mean, not the median.

How we counted

Frequency and difficulty come from this skill's questions across our assembled full-length Digital SAT forms; the practice count is how many drills of these types are in our bank.

4 question types in Statistics & Data Distribution

Common questions

How does sample size affect the margin of error?

A larger random sample gives a smaller margin of error and a more precise estimate. Smaller samples produce wider margins. Thinking a bigger sample widens the margin is the most common error.

When is the mean pulled away from the median?

When a distribution is skewed or has outliers, the mean shifts toward the long tail while the median stays central. Comparing them tells you the direction of the skew.

What conclusion can I draw from a sample?

Only one about the population that was randomly sampled, stated within the margin of error. Extending it to a broader group, or treating the estimate as exact, is not supported.

Practice Statistics & Data Distribution the way it is tested

Start with the free 16-question diagnostic, then drill any of these types with step-by-step reasoning.