Plotting Data

Student Summary

Histograms show us how measurements of a single attribute are distributed. For example, a veterinarian saw 25 dogs in her clinic one week. She measured the height and weight of each dog.

This histogram shows how the weights of the dogs are distributed.

Histogram from 0 to 112 by 16’s. Dog weight, pounds. Beginning at 0 up to but not including 16, height of bar at each interval is 6, 8, 2, 5, 2, 1, 1.

This histogram shows how the heights of the dogs are distributed.

Histogram from 6 to 30 by 3’s. Dog height, inches. Beginning at 6 up to but not including 9, height of bar at each interval is 1, 4, 5, 2, 6, 3, 2, 2.

These histograms tell us how the weights of the dogs and how the heights of dogs were distributed. But, they do not give any evidence of a connection between a dog’s height and its weight.

Scatter plots allow us to investigate possible connections between two attributes. In this example, each plotted point corresponds to 1 of the 25 dogs, and its coordinates tell us the height and weight of that dog. Examination of the scatter plot allows us to see a connection between height and weight for the dogs. 

Scatterplot.
A scatterplot. Horizontal, from 6 to 30, by 3’s, labeled dog height, inches. Vertical, from 0 to 112, by 16’s, labeled dog weight, pounds. 24 data points.  Trend upward and to right.

Visual / Anchor Chart

Standards

Building On
6.SP.4

Display quantitative data in plots on a number line, including dot plots, and histograms.

Addressing
8.SP.1

Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.