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Understanding Skewness and Outliers in Data: Mean vs Median, Summaries of Mathematical Statistics

The concept of skewness in data distribution and the importance of using the mean or median as a measure of central tendency depending on the presence of outliers. It also discusses the role of standard deviation and interquartile range in measuring spread. Examples of symmetric, skewed left, and skewed right distributions, and provides guidelines for choosing between mean and median based on the shape and presence of outliers.

Typology: Summaries

2021/2022

Uploaded on 09/27/2022

parvini
parvini 🇺🇸

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bg1
SKEWED TO THE RIGHT
-Here the mean is
pulled right by the
large values.
-The mean is larger
than the median and
not a good measure
of center.
SYMMETRIC
-Mean and the
Median should be
approximately the
same value
SKEWED LEFT
-Mean is pulled
lower by the
smaller values in
the plot
-The mean is
smaller than the
median and is not
a good measure of
center.
pf3
pf4

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SKEWED TO THE RIGHT-^ Here the mean ispulled right by thelarge values.-^ The mean is largerthan the median andnot a good measureof center.

SYMMETRIC-^ Mean and theMedian should beapproximately thesame value

SKEWED LEFT-^ Mean is pulledlower by thesmaller values inthe plot-^ The mean issmaller than themedian and is nota good measure ofcenter.

UPPER OUTLIERS-^ Pulls Mean higher-^ Pulls St. Dev.higher-^ Pulls Max higher-^ Pulls Range higher LOWER OUTLIERS-^ Pulls Mean lower-^ Pulls St. Dev.higher-^ Pulls Min lower-^ Pulls Range higherMedianQ1Q3IQR

Unaffected by outliersResistant

Shape •^ Same as before •^ Skewed Left; Skewed Right; Symmetric; Uniform •^ Unimodal; Bimodal; Multimodal; Uniform •^ Outliers?

^ Mean or Median^ If Symmetric, Unimodal, with no big Outliers– Use the Mean `^ If Skewed or has big Outliers– Use the Median

  • Skewed LeftUnimodalOutliers below LF of 63.5Centered at the Median of 91Spread with an IQR of 13Range from 55 to
  • Skewed RightUnimodalNo OutliersCentered at the Median of 41Spread with an IQR of 70Range from 10 to