Scatter Plots, Covariance & Linear Association

Describe paired numerical data using scatter-plot structure and covariance. Calculate sample and population forms, track product units, and analyze shifts, rescaling, pairing integrity, curved relationships and clustered data. Prerequisites: means, centered deviations and variance. Examples build from direct calculations to diagnostic interpretation of numerical and visual summaries. Includes single-select and multiselect practice with worked explanations and misconception-specific feedback.

Further reading and method references:

• NIST: scatter plots
• NumPy: covariance definitions