### Clarifications

*Clarification 1*: Instruction includes fitting a linear function both informally and formally with the use of technology.

*Clarification 2*: Problems include making a prediction or extrapolation, inside and outside the range of the data, based on the equation of the line of fit.

**Subject Area:**Mathematics (B.E.S.T.)

**Grade:**912

**Strand:**Data Analysis and Probability

**Date Adopted or Revised:**08/20

**Status:**State Board Approved

## Related Courses

## Related Access Points

## Related Resources

## Formative Assessments

## Lesson Plans

## Perspectives Video: Experts

## Perspectives Video: Professional/Enthusiasts

## STEM Lessons - Model Eliciting Activity

Students will apply skills (making a scatter plot, finding Line of Best Fit, finding an equation and predicting the y-value of a point on the line given its x-coordinate) to a fuel efficiency problem and then consider other factors such as color, style, and horsepower when designing a new coupe vehicle.

Model Eliciting Activities, MEAs, are open-ended, interdisciplinary problem-solving activities that are meant to reveal studentsâ€™ thinking about the concepts embedded in realistic situations. Click here to learn more about MEAs and how they can transform your classroom.

## MFAS Formative Assessments

Students are asked to interpret the meaning of the constant term in a linear model.

Students are asked to interpret the line of best fit, slope, and *y*-intercept of a linear model.

Students are asked to informally fit a line to model the relationship between two quantitative variables in a scatterplot, write the equation of the line, and use it to make a prediction.

Students are asked to interpret the intercept of a linear model of life expectancy data.

Students are asked to interpret the meaning of the slope of the graph of a linear model.

Students are asked to interpret the meaning of the slope of the graph of a linear model.

Students are asked to use a linear model to make and interpret predictions in the context of the data.

Students are asked to use a linear model to make a prediction about the value of one of the variables.