Scatter Plots & Line of Best Fit Cheat Sheet

A printable reference covering scatter plots, correlation, trend lines, slope, intercepts, and the line of best fit for grades 7-10.

Download PNG

Related Tools

Related Labs

Related Worksheets

Related Infographics

Scatter plots show the relationship between two numerical variables by graphing paired data as points. This cheat sheet helps students identify patterns, describe association, and decide whether a line of best fit is reasonable. These skills are useful for making predictions from data in science, business, sports, and everyday comparisons.

Key Facts

A scatter plot graphs ordered pairs $\left(x, y\right)$ to show how two numerical variables may be related.
A positive association means that as $x$ increases, $y$ tends to increase.
A negative association means that as $x$ increases, $y$ tends to decrease.
No association means the points do not show a clear upward or downward pattern.
A line of best fit is often written as $y = mx + b$ , where $m$ is the slope and $b$ is the $y$ -intercept.
The slope of a line is $m = \frac{y_2 - y_1}{x_2 - x_1}$ , which represents the rate of change between two points.
The $y$ -intercept $b$ is the predicted value of $y$ when $x = 0$ .
Interpolation predicts a value inside the data range, while extrapolation predicts a value outside the data range.

Vocabulary

Scatter plot: A graph that displays paired numerical data as points $\left(x, y\right)$ on a coordinate plane.
Association: The overall relationship or pattern between the two variables in a scatter plot.
Correlation: A description of the direction and strength of the relationship between two numerical variables.
Line of best fit: A straight line that closely follows the overall trend of the data points in a scatter plot.
Slope: The rate of change of a line, calculated by $m = \frac{y_2 - y_1}{x_2 - x_1}$ .
Outlier: A data point that is far away from the general pattern of the rest of the data.

Common Mistakes to Avoid

Confusing positive and negative association is wrong because the direction depends on whether $y$ tends to increase or decrease as $x$ increases.
Drawing a line of best fit through the most points is wrong because the line should balance the data with about the same number of points above and below it.
Using only one data point to make a prediction is wrong because predictions should be based on the overall trend, not a single value.
Ignoring outliers is wrong because an outlier can strongly affect the position and slope of a line of best fit.
Extrapolating too far beyond the data is risky because the trend may not continue outside the observed range.

Practice Questions

1 A line of best fit passes through $\left(2, 5\right)$ and $\left(6, 13\right)$ . Find the slope $m$ .
2 A line of best fit is $y = 3x + 4$ . Predict $y$ when $x = 7$ .
3 A scatter plot comparing hours studied and test score shows points rising from left to right. Describe the association and explain what it means.
4 Why is a prediction using interpolation usually more reliable than a prediction using extrapolation?

Sign in to save