AP Statistics / Exploring One-Variable Data and Collecting Data
Lesson
Reading one-variable distributions
Choose a display, then describe shape, center, spread, and unusual values.
Learning goals
- Match a variable type to an appropriate graph and summary.
- Write a short description of a distribution in context.
Explanation
Start with the variable. Counts in named categories belong on a bar chart or table. Measurements on a number line belong on a histogram, boxplot, or stemplot. The display is a tool, not the answer.
A useful description names shape, a measure of center, a measure of spread, and any unusual points. Mean and standard deviation fit fairly symmetric data. Median and IQR hold up better when the tail is long or a few values sit far from the rest.
Key terms
- Distribution. The pattern of values a variable takes, including shape, center, spread, and unusual points.
- Standard deviation. A typical distance of values from the mean, useful when the distribution is not badly skewed.
Common mistakes
- Reporting only the mean when the graph is clearly skewed.
- Calling a bar chart a histogram because both use bars.
Practice
Original Marlow Works items. Check the answer explanation after you try.
A reporter stands at one grocery-store exit and asks shoppers whether they support a new park tax. Why is this a poor way to estimate citywide support?
Original Marlow Works item — not a College Board question.
Take your time—this is practice, not a test.
Answer explanation
Commute times for 40 students are strongly right-skewed. Which pair of numbers should you lead with, and why?
Answer. Median and IQR, because they are less pulled by the long right tail.
The mean and standard deviation chase extreme late commutes and can overstate a typical trip.
Related resources
External links with reuse status. Marlow Works is independent and does not copy restricted exam or textbook material.
Official / link only
AP Statistics course page
Official revised 2026–27 five-unit framework.
College Board · All rights reserved · accessed 2026-10-01
Open sourceCC BY — attribution required
Collaborative Statistics
Open statistics text for distributions, probability, and inference.
Open Textbook Library listing · CC BY · accessed 2026-10-01
Open source