Analyse scatter plots for bivariate data to find connections between two quantities; find patterns such as outliers, clusters, linear and nonlinear association. Develop a basic understanding that straight lines can indicate a relationship between two quantitative variables. Look at scatter plots; if there's a suggestion of a linear relationship, draw a straight line to approximate the relationship and inspect the fit of the model by seeing how close the data points are to the line.

Use a linear model equation to address problems related to bivariate data, and understand what the slope and intercept signify. As an example, in a biological experiment, a slope of 1.5 cm/hr could mean that every extra hour of sunlight increases the mature plant height by 1.5 cm.

Comprehend that associations can be found in bivariate categorical data by visualizing frequencies in a two-way table. Make and interpret a two-way table that summarises data collected on two categorical variables from the same subjects. Use relative frequencies from rows or columns to indicate potential relationships between variables. As an example, collect data on the presence of a curfew and assigned chores among your classmates to explore possible linkages.