Lesson 6 of 8 · All lessons in this module
- Mean, median, mode and outliers
- Quantiles, box plots and their uses
- Range, mean absolute deviation, variance and standard deviation
- Target downside deviation and coefficient of variationVideo lesson
- Skewness and kurtosisVideo lesson
- Scatter plots, covariance and correlation
- Limits of correlation analysis
- Integrated cases: describing one return series from raw data
Lesson 6 of 8 · 14 min
Scatter plots, covariance and correlation
Covariance shows whether two variables move together; correlation rescales it to a unit-free number between −1 and +1 that measures the strength of the linear link.
In short
- A scatter plot shows each pair of observations as a point: look for the pattern, how tightly points cluster, the range and any outliers.
- Sample covariance averages the cross-products of deviations, dividing by n − 1. Its sign shows direction, but its size depends on the units.
- Correlation = covariance ÷ (), always between −1 and +1.
- +1 or −1 means all points lie on one straight line, whatever its slope; 0 means no linear relation.
- Correlation always has the same sign as covariance; the signs of the means do not matter.
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