Scatterplots intro

A scatterplot is a graphical representation of two variables, showing the relationship between them using points on a Cartesian plane.

A positive correlation indicates that as one variable increases, the other variable also increases.

A negative correlation indicates that as one variable increases, the other variable decreases.

No correlation means there is no discernible relationship between the two variables; changes in one do not affect the other.

Outliers can skew the perception of the relationship between variables, potentially leading to incorrect conclusions.

Scatterplots are used to visually assess the relationship between two quantitative variables, helping to identify trends, correlations, and outliers.

A linear association shows a straight-line relationship between variables, while a non-linear association shows a curved relationship.

An outlier is identified as a point that lies significantly outside the overall pattern of the data, often distant from other points.

The slope indicates the direction and strength of the relationship between the two variables; a steeper slope indicates a stronger relationship.

A regression line is a straight line that best fits the data points in a scatterplot, used to predict values of one variable based on another.