Creating and Reading Scatter Plots
This Grade 11 math skill from enVision Algebra 1 teaches students to create and read scatter plots. A scatter plot graphs data as individual points on a coordinate plane, where each point represents an ordered pair (x, y). Students learn to plot data sets, choose appropriate scales, label axes, and read patterns from completed scatter plots. Scatter plots are a fundamental tool for visualizing whether a relationship exists between two variables — whether values tend to increase together, decrease together, or show no clear pattern.
Key Concepts
A scatter plot is a graph that displays data as points plotted on a coordinate plane, where each point represents a pair of values $(x, y)$. Scatter plots help visualize the relationship between two variables and show whether there is a pattern or trend in the data.
Common Questions
What is a scatter plot?
A scatter plot is a graph on a coordinate plane where each data point is plotted as an individual (x, y) pair. Together, the plotted points reveal whether and how two variables are related.
How do you create a scatter plot?
To create a scatter plot: choose appropriate scales for both axes, label each axis with its variable name and units, then plot each (x, y) data pair as a single point on the coordinate plane. Do not connect the points.
What can you learn from reading a scatter plot?
A scatter plot shows whether two variables have a positive association (both increase together), negative association (one increases as the other decreases), or no clear association (points are randomly scattered with no pattern).
Why are scatter plots useful in data analysis?
Scatter plots visually display the relationship between two quantitative variables, making it easy to spot trends, clusters, outliers, and patterns that raw numbers in a table might not reveal.
How do scatter plots connect to regression in Algebra 1?
In Algebra 1, after creating a scatter plot, students often draw a line or curve of best fit through the data, then use regression equations to make predictions and measure the strength of the relationship with R².