Bivariate Data and Constructing Scatter Plots

Property Bivariate data consists of pairs of values for two different variables. A scatter plot is a graph that displays these pairs of data as points $(x, y)$ on a coordinate plane to show the relationship between the two variables. $x$ axis: Represents the independent variable (the input or explanatory variable). $y$ axis: Represents the dependent variable (the output or response variable). Axis Break: A symbol used on an axis to indicate that a range of values starting from 0 has been skipped to avoid empty space.

Examples For data comparing "Hours Studied" and "Test Score", "Hours Studied" is the independent variable ($x$ axis) and "Test Score" is the dependent variable ($y$ axis). A single data point could be $(3, 85)$, representing 3 hours of study and a score of 85. If a dataset of weights ranges from 120 lbs to 160 lbs, place an axis break between 0 and 120 on the axis, then use consistent increments of 10.

Explanation To construct a scatter plot, first determine which variable is independent ($x$ axis) and which is dependent ($y$ axis). Next, choose a scale with consistent increments that covers the entire range of your data. If data values start far from zero, an axis break skips the empty space, making the pattern in the data much easier to see. Finally, plot each observation as an ordered pair $(x, y)$.