Positive, Negative & No -Correlations

A positive correlation is a relationship between two variables where, as one variable increases, the other variable also increases.

A negative correlation is a relationship between two variables where, as one variable increases, the other variable decreases.

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

In a scatter plot, a positive correlation is identified by points that trend upwards from left to right.

In a scatter plot, a negative correlation is identified by points that trend downwards from left to right.

A scatter plot with no correlation shows points that are randomly scattered without any discernible pattern.

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

You can use a trend line to predict values by extending the line and finding where it intersects with the value of interest.

An example of a positive correlation is the relationship between hours studied and test scores; generally, more study time leads to higher scores.

An example of a negative correlation is the relationship between the amount of exercise and body weight; typically, more exercise leads to lower body weight.