lesson
Comparing Data Sets with Different Shapes and Outliers
Compare two data sets that differ in shape and presence of outliers, choosing appropriate statistics.
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This lesson is part of a track
Public learning track
Comparing Distributions and Analyzing Outliers
9 lessons
Goal
Learners will compare data sets by analyzing distribution shapes, identifying outliers using the 1.5 × IQR rule, and evaluating the impact of extreme values.
9 lessons
0 of 9 done
- Comparing Two Data Sets Using Center and SpreadUp next
- Identifying Distribution Shapes: Symmetric, Skewed, UniformNot started yet
- How Skewness Affects Mean vs. MedianNot started yet
- What Is an Outlier? Identifying Extreme ValuesNot started yet
- The 1.5 × IQR Rule for Detecting OutliersNot started yet
- Effects of Outliers on the Mean and Standard DeviationNot started yet
- Effects of Outliers on the Median and IQRNot started yet
- Comparing Data Sets with Different Shapes and OutliersYou are here
- Deciding Whether to Exclude Outliers from AnalysisNot started yet
Learning standards covered
HSS.ID.A.3Common Core State Standards · Math · 11th GradeInterpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).
Open Global Standard:OGM.13.STA.2
HSS.ID.A.2Common Core State Standards · Math · 11th GradeUse statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.
Open Global Standard:OGM.13.STA.1
OGM.13.STA.2OGM.13.STA.1