Scatter Plot & Association

A scatter plot is a graph that shows the relationship between two quantitative variables by displaying data points on a two-dimensional axis.

A positive association indicates that as one variable increases, the other variable also tends to increase.

A negative association indicates that as one variable increases, the other variable tends to decrease.

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

An outlier is a data point that differs significantly from other observations in the dataset, often appearing far away from the trend of the data.

A linear association can be identified if the data points roughly form a straight line, either sloping upwards (positive) or downwards (negative).

A nonlinear association occurs when the relationship between the variables cannot be accurately represented by a straight line.

A strong association means that the data points are closely clustered around a line or curve, indicating a clear relationship between the variables.

A weak association means that the data points are more spread out and do not closely follow a line or curve, indicating a less clear relationship.

Scatter plots are used to visually assess the relationship between two variables, helping to identify trends, correlations, and potential outliers.