A correlation coefficient is a statistical measure that quantifies the degree to which two variables are related or move together. In other words, it assesses the strength and direction of a linear relationship between two variables. The correlation coefficient is denoted by the symbol r.

The value of the correlation coefficient r ranges from -1 to 1:

• $1$ indicates a perfect positive correlation, meaning that as one variable increases, the other variable also increases proportionally.
• $-1$ indicates a perfect negative correlation, meaning that as one variable increases, the other variable decreases proportionally.
• $0$ indicates no linear correlation between the variables. However, it’s important to note that there could still be other types of relationships between the variables that are not captured by the correlation coefficient.

Interpreting the correlation coefficient:

• If r is close to 1 or -1, it indicates a strong correlation.
• If r is close to 0, it suggests a weak or no linear correlation.

It’s important to note that correlation does not imply causation. Even if two variables are correlated, it does not necessarily mean that changes in one variable cause changes in the other; there could be other factors at play.

For a demonstration in performing this analysis in SPSS, click https://youtu.be/PJviUilXfi0?si=9r8HuGHQ1FNdY5ML

For a demonstration in performing this analysis in Excel, click here: https://youtu.be/JO-Gc5bEG70?si=UrddZc3vR4kgz6fE