In this Grade 6 lesson from Big Ideas Math Advanced 1, Chapter 10, students learn to identify and describe the shapes of data distributions — specifically skewed left, skewed right, symmetric, and uniform distributions — using dot plots and histograms. Students explore how the position of a distribution's "tail" determines whether it is skewed and how symmetry appears when the left and right sides mirror each other. The lesson also connects distribution shape to appropriate measures of center and variation, helping students decide when the mean or median best represents a data set.
Section 1
Identifying Distribution Shapes
The shape of a histogram tells a lot about the data distribution.
A histogram can be symmetric (both sides look like mirror images), skewed left (the tail extends toward smaller values on the left), or skewed right (the tail extends toward larger values on the right).
We identify skewness by looking at which direction the longer tail points.
Section 2
Identifying Uniform Distributions
A uniform distribution occurs when all values or intervals have approximately the same frequency, resulting in dots or bars that are roughly equal in height across the entire range of data.
Section 3
Relationship Between Distribution Shape and Measures of Center
The shape of a distribution determines the relationship between the mean and median, which helps us choose the most appropriate measure of center.
Skewed Left: The mean is pulled to the left of the median by extreme low values. The median is a better measure of center because it is not affected by the outliers.
Book overview
Jump across lessons in the current chapter without opening the full course modal.
Continue this chapter
Expand to review the lesson summary and core properties.
Section 1
Identifying Distribution Shapes
The shape of a histogram tells a lot about the data distribution.
A histogram can be symmetric (both sides look like mirror images), skewed left (the tail extends toward smaller values on the left), or skewed right (the tail extends toward larger values on the right).
We identify skewness by looking at which direction the longer tail points.
Section 2
Identifying Uniform Distributions
A uniform distribution occurs when all values or intervals have approximately the same frequency, resulting in dots or bars that are roughly equal in height across the entire range of data.
Section 3
Relationship Between Distribution Shape and Measures of Center
The shape of a distribution determines the relationship between the mean and median, which helps us choose the most appropriate measure of center.
Skewed Left: The mean is pulled to the left of the median by extreme low values. The median is a better measure of center because it is not affected by the outliers.
Book overview
Jump across lessons in the current chapter without opening the full course modal.
Continue this chapter