1. The problem is to understand what correlation means in statistics. 2. Correlation measures the strength and direction of a linear relationship between two variables. 3. The formula for the Pearson correlation coefficient $r$ is: $$r = \frac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum (x_i - \bar{x})^2 \sum (y_i - \bar{y})^2}}$$ where $x_i$ and $y_i$ are data points, and $\bar{x}$ and $\bar{y}$ are the means of $x$ and $y$ respectively. 4. Important rules: - $r$ ranges from $-1$ to $1$. - $r = 1$ means perfect positive linear correlation. - $r = -1$ means perfect negative linear correlation. - $r = 0$ means no linear correlation. 5. Correlation does not imply causation; it only indicates how variables move together. 6. In simple terms, correlation tells us if two things tend to increase or decrease together and how strongly. Final answer: Correlation is a statistical measure that quantifies the degree to which two variables are linearly related.