Mathematics | Grade : 8
Domain - Statistics and Probability
Cluster - Investigate patterns of association in bivariate data.
[8.SP.A.1] - Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
- Bivariate data
Pairs of linked numerical observations. Example: a list of heights and weights for each player on a football team. - Linear association
Two variables have a linear association if a scatter plot of the data can be well approximated by a line. - Non-linear association
The relationship between two variables is nonlinear if the change in the second is not simply proportional to the change in the first, independent of the value of the first variable. - Scatter plot
A graph in the coordinate plane representing a set of bivariate data. For example, the heights and weights of a group of people could be displayed on a scatter plot.
[8.SP.A.2] -
Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.