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AP® Statistics · Unit 1 · Topic 1.6

Descriptions for One Quantitative Variable Distributions: Revision Notes (Statistics 1.6)

One-page recap of describing a quantitative distribution: skewed or symmetric, unimodal, bimodal or uniform, outliers, gaps and clusters, centre and spread, and using a graph to judge a claim.

Short on time? This page is the recap. For explanations and worked examples, use the full study guide.

Recap

  • A full description has four parts: shape, centre, variability and unusual features.
  • Every part is in context: the variable, the individuals and the units.
  • In this topic, centre and spread are estimated from the graph. Exact calculations come in Topic 1.7.
  • A graph can support or reject a claim when you quote counts or values from it.

Key relationships

Feature What you see on the graph Word to use
Shape (symmetry) Longer tail towards larger values Skewed right (positively skewed)
Shape (symmetry) Longer tail towards smaller values Skewed left (negatively skewed)
Shape (symmetry) Two halves roughly mirror images Approximately symmetric
Shape (peaks) One main peak Unimodal
Shape (peaks) Two clear peaks Bimodal
Shape (peaks) Bars or values about equally frequent, no clear peak Approximately uniform
Unusual feature Value unusually far from the rest Possible outlier
Unusual feature Stretch of the scale with no data Gap
Unusual feature Group of values close together, set apart by gaps Cluster
Centre Middle value of the ordered data (on a histogram, the bin that holds it) Median (estimate)
Variability Smallest to largest value, and where most values lie Range; “most values between … and …”

Assumptions and conventions

  • The graph shows one quantitative variable measured in the same units.
  • Say “approximately” symmetric or uniform: real data are never exact.
  • On a histogram you cannot read individual values. Use bin edges and counts.
  • Without a numerical rule, call an unusual value a possible outlier.

Mistakes to avoid

  1. Naming skew after the peak. A peak on the left with a long right tail is skewed right.
  2. Missing a part. Shape alone is not a description; include centre, spread and unusual features.
  3. No context or units. “Skewed right” alone earns little.
  4. Calling a cluster an outlier. A large group beyond a gap is a cluster.
  5. Claiming an exact median from a histogram. Name the bin that contains it.
  6. Judging a claim by appearance. Quote a count or percentage and compare it with the claim.

Quick self-check

  1. A histogram has its tallest bar near the right end and bars that slowly shrink towards the left. Name the shape. (Unimodal and skewed left: the longer tail is towards smaller values.)
  2. Six bins have frequencies 2, 9, 4, 1, 8, 3. Describe the number of peaks. (Bimodal: clear peaks in the 2nd bin (9) and the 5th bin (8).)
  3. Data (seconds): 12, 15, 18, 19, 21, 22, 22, 25, 47. Name any unusual features. (A gap from 26 to 46 seconds and a possible outlier at 47 seconds, which is 22 seconds above the next largest value.)

Next: practice questions.

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