Correlation is a statistical measure that describes the extent to which two variables change together. A positive correlation means that as one variable increases, the other tends to increase, while a negative correlation means that as one variable increases, the other tends to decrease.

The correlation coefficient (r) quantifies the strength and direction of a linear relationship between two variables, ranging from -1 to 1. A value of 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no correlation.

An r value of 0 indicates no correlation between the two variables, meaning that changes in one variable do not predict changes in the other.

An r value of 0.9 indicates a strong positive correlation, meaning that as one variable increases, the other variable also tends to increase significantly.

An r value of -0.9 indicates a strong negative correlation, meaning that as one variable increases, the other variable tends to decrease significantly.

A scatter plot is a graphical representation of two variables, where each point represents an observation. It helps visualize the relationship between the variables.

A weak positive correlation on a scatter plot appears as points that are loosely clustered in an upward trend, indicating that as one variable increases, the other variable tends to increase, but not strongly.