Scatter Plots

A scatter plot is a graph that shows the relationship between two quantitative variables by displaying data points on a two-dimensional axis.

A trend line is a straight line that best represents the data points in a scatter plot, indicating the general direction of the relationship between the variables.

You can use a scatter plot to make predictions by extending the trend line to estimate values for variables not directly measured.

A positive correlation indicates that as one variable increases, the other variable also tends to increase.

A negative correlation indicates that as one variable increases, the other variable tends to decrease.

No correlation means there is no apparent relationship between the two variables; changes in one do not affect the other.

You identify the type of correlation by observing the direction of the trend line: upward for positive, downward for negative, and scattered for no correlation.

Scatter plots are used to visually assess relationships between variables, identify trends, and make predictions based on data.

Outliers are data points that differ significantly from other observations; they can affect the trend line and overall analysis.

The strength of a correlation can be determined by how closely the data points cluster around the trend line; tighter clusters indicate stronger correlations.