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3 topics that must be addressed:. Describing Distributions . Center. Shape. Spread. Shape. Always describe the basic shape of the distribution. Symmetric – left and right sides are mirror images, or approximate (since we’re dealing with real data).
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3 topics that must be addressed: Describing Distributions Center Shape Spread
Shape • Always describe the basic shape of the distribution. • Symmetric – left and right sides are mirror images, or approximate (since we’re dealing with real data)
Skewed Left – majority of the data is on the right side but trails out to the left • Skewed Right – majority of the data is on the left side but trails out to the right
Unimodal – one major mode where the data is collected around • Bimodal – two major modes • Multimodal – multiple modes • Uniform – data is flat
Also mention any unusual features • Outliers – observations away from the main distribution. • Gaps- Spaces between clumps of data
Center • Mean or Median • Right now, just approximate Spread • Will use either Std. deviation or IQR (will learn later) • Always list the range of the data (min, max).
Example The distribution is unimodal and skewed to the right. The center is around 15. The range is (0, 60). There is a gap in the 55 to 60 bin. The distribution is unimodal and approximately symmetric. The center is around 5 or6. The range is (0, 17). There is a possible outlier at 16.
