Line of Best Fit Teacher Resources

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Learners graph points on a coordinate plane. For this algebra lesson, students analyze the points on a coordinate plane finding the line of best fit. They compare age in years and arm span in inches.
Start this lesson plan by having your class generate their own data and determine the line of best fit relating their height and shoe size. Interpret the meaning of the slope and y-intercept in the context of the problem and use the equation to estimate shoe size based on height. Discuss the accuracy of their model and introduce the concept of residuals. Follow up with a two-problem worksheet where learners can practice calculating residuals for given data sets. The first has a step-by-step guide to the process. Included on the handout are directions on how to graph residuals on a TI calculator. 
Your class will generate their own data relating the number of people to the time it takes to do a human wave. Once data is collected, a line of best fit is found and used to estimate how long it would take for the entire student body to produce one cycle of the wave in the school gym. How fun would it be to actually have your school do the wave and compare the actual time to the calculated estimate!
Your class can learn about positive and negative correlation by exploring the relationship between pairs of quantitative variables. Start with a description of the variables and hypothesize if a strong or weak correlation exists. Make specific data available and have them use scatter plots to help support their claim. Use graphing calculators to find the associated line of best fit and calculate the corresponding r-value. Have students present their work and discuss if the correlation coefficient supports their original hypothesis and if a linear regression is the best model for the data.
Students explore the concept of linear regression. In this linear regression lesson, students find the line of best fit for a set of data pertaining to a frog population. Students use their line of best fit to predict the frog population in a certain year.
Adjust this lesson to fit either beginning or more advanced learners. Build a scatter plot, determine appropriate model (linear, quadratic, exponential), and then extend to evaluate the model with residuals. This problem uses real-world data and challenges one to make predications based on the model. 
This math packet includes four different activities which puts linear equations and line of best fit in the context of real world applications. Each activity uses a different linear math modeling equation and asks the learners to complete several questions. And grading will be a breeze, because answers are included.
In the context of western wildfires, mathematicians discover how a variable can be used to solve problems. They read about wildfires, construct variable equations, and then learn to graph results in scatter-plot fashion to determine if there are relationships between flame length and vegetation type. This resource comes complete with colorful, professionally-designed handouts that fully support the rich content.
Seventh graders use graphs to interpret data.  For this linear equation lesson, 7th graders record the thickness of candy on a worksheet.  Students start to eat their candy and measure it again. Students continue until the candy is gone.  Students create a scatter plot to graph their data and answer questions to develop an equation.
Learners use a stopwatch to collect information for a scatterplot.   In this fastest legs lessons, students collect data through the taking of measurements, create and find a median number. Learners develop an equation and answer questions based on their data.
Middle schoolers determine the density of 1 drop of water. In this determining density lesson plan, students determine the mass and volume of a drop of water in the lab using appropriate lab techniques and calculate the density of a drop of water.
Math whizzes utilize spreadsheets to examine linear modeling. They roll marbles down a ramp from three different heights and measure how far they roll. They use Excel to record their data and create a plot of their data.
Eleventh graders determine a line of regression and coefficient of correlation for bivariate data.  In this Algebra II lesson, 11th graders determine the relationship between the regression line and the correlation coefficients.  This review lesson provides an opportunity for students to learn the material in a different way, including visually and symbolically.
Students explore the concept of scatter plots.  In this scatter plots lesson, students collect data by simulating a seesaw.  Students collect data about distance and weight.  Students plot the data on their graphing calculator and find a line of best fit to model the data.
For this graphing and analyzing worksheet, 9th graders first state if each graph represents a linear or nonlinear relationship. Second, they create a difference table for each set of data presented and determine whether it represents a linear or nonlinear relationship. Next, students create a scatter plot for the data presented in each table and determine the curve of best fit.
Students investigate data collection and analysis.  In this Algebra I lesson, students create a scatter plot and find the equation of best fit in a simulation of a leaking water pipe.
Ninth graders explore regression equations.  In this Algebra I instructional activity, 9th graders create lists of data points and determine the regression equation of the line that best fits the data points.  In this second part to the instructional activity, students investigate the mathematics behind how the linear regression is determined.
Students solve equations dealing with best fit lines. In this algebra lesson, students solve problems by analyzing data from a scatterplot, and define it as positive, negative or no correlation. They classify slopes the same way as positive, negative, zero or undefined.
Eighth graders conduct an experiment that is examining an equation that is drawn from collecting data measuring the acceleration and distance traveled by Hot Wheel cars. The equation that is drawn is used to make predictions of future outcomes.
Students explore the concept of linear regression. In this linear regression lesson, students drive a remote control car and collect data on its speed over time. Students make a scatter plot and determine the line of best fit using linear regression.

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