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Shapes of distributions: Key vocabulary terms

Shapes of distributions: Key vocabulary terms. S-012. 15. Here is a set of scores. Let’s make a graph. 15. A dot represents the score for the first student. 15. 15. 15. We can see where the scores start to pile up. We get a picture of the distribution of the scores.

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Shapes of distributions: Key vocabulary terms

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  1. Shapes of distributions:Key vocabulary terms S-012

  2. 15 Here is a set of scores. Let’s make a graph.

  3. 15 A dot represents the score for the first student.

  4. 15

  5. 15

  6. 15 • We can see where the scores start to pile up. • We get a picture of the distribution of the scores.

  7. When we have a large number of scores, it is convenient to draw a smooth curve to depict the distribution. 15 • Drawing a curve is just a quick way to show the shape of the distribution. • It is really just showing us where the individual scores fall. • The smooth curve may sometimes be a bit too simple – it can obscure some details. • Not every distribution can be described by a smooth curve.

  8. Normal, bell-shaped • Symmetric • Mean=median=mode • Mound-shaped • Symmetric • Uni-modal • Approximately normal • Skewed to the right • Positively skewed • Not symmetric (Asymmetric) • Mean > Median * • Top 50% more spread out then bottom 50% • Skewed to the left • Negatively skewed • Not symmetric (Asymmetric) • Mean < Median* • Bottom50% more spread out than top 50% * Almost always true with continuous variables. Sometimes not true with discrete variables, but mostly a good rule to use.

  9. J-shaped Bi-modal Uniform (rectangular) U-shaped

  10. Normal curve is our reference. Kurtosis: refers to how “sharply peaked” or “flat” the distribution is. Leptokurtic – a sharper point, a higher peak around the mean. (Lepto = “thin” or “narrow”) Platykurtic – a flatter peak around the mean. (Platy = “flat”) Definitely drop some of these terms into your dinner conversation. You will dazzle your friends when you say “platykurtic.”

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