Regression line

Definition

A regression line is a straight line that best fits the data points on a scatter plot, showing the relationship between two variables. It is used to predict values and determine trends in data sets.

5 Must Know Facts For Your Next Test

1. The equation of a regression line is typically written as y = mx + b, where m is the slope and b is the y-intercept.
2. The slope (m) indicates the rate of change between the variables, showing how much y changes for each unit increase in x.
3. The y-intercept (b) represents the value of y when x is zero.
4. Regression lines are used to make predictions based on existing data points by extending the line beyond observed values.
5. The accuracy of a regression line can be assessed using measures like R-squared (R²), which indicates how well the line fits the data.

Review Questions

• What does the slope (m) represent in the equation of a regression line?
• How can you use a regression line to make predictions about future data points?
• What does an R-squared value tell you about a regression line?

Related terms

Scatter Plot: A graph that shows individual data points plotted along two axes to visualize relationships between variables.

Correlation: A statistical measure that describes the strength and direction of a relationship between two variables.

Residuals: The differences between observed values and predicted values on a regression line, indicating prediction errors.