Scatter plots and Association

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

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 predictable relationship between the two variables; the data points do not show any pattern.

A positive correlation can be identified by a pattern where the data points slope upwards from left to right.

A negative correlation can be identified by a pattern where the data points slope downwards from left to right.

Scatter plots are used to visually represent the relationship between two variables and to identify trends or correlations.

An example of a positive correlation is the relationship between study time and test scores; as study time increases, test scores tend to increase.

An example of a negative correlation is the relationship between the amount of exercise and body weight; as exercise increases, body weight tends to decrease.

An example of no correlation is the relationship between shoe size and intelligence; there is no predictable pattern between these two variables.