March 21, 2012

In this lesson, students explore the relationship between age and height in order to help a hypothetical student predict his height in two years. Students will examine data that will enable them to create a scatterplot and approximate a line of best fit. The scatterplot and line of best fit will be used to predict height. The slope of the line of best fit will be interpreted in context.

- Mathematics > General
- Mathematics > Applied Mathematics
- Mathematics > Data Analysis & Probability
- Mathematics > Problem Solving
- Mathematics > Statistics

- Grade 6
- Grade 7
- Grade 8

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.

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.

Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept.

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.

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.

Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept.