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Course, Subject

Algebra I (Next Generation), Algebra II (Next Generation), Math, Science & Technology, Mathematics (NYS P-12 Next Generation)

Description

The regression applet is designed to allow the user to plot a bivariate data set, determine the line of best fit for their data, and then check the accuracy of their line of best fit. This activity determines the correlation coefficient, r, for the true lines of best fit and also exposes students to residuals. This activity would work well in groups of two or three for about 10-15 minutes.

Correlation and regression are used regularly in statistical analysis. Correlation is used to see if a relationship exists between two variables and can be used to answer questions. If a relationship is found then correlation can be used to determine how strong the relationship is. Once a correlation has been discovered, regression is used to find the equation used to relate the two variables. This equation can tell you if the two variables are positively or negatively related.

This activity can be used to:

• Teach students about how data influences the line of best fit
• Provide students with practice in determining the line of best fit for some data
• Introduce students to residuals
• Allow students exploration with the linear correlation coefficient, r

Virtual Manipulative

Click here for this interactive resource.

Content Provider

The Shodor Foundation is a non-profit research and education organization dedicated to the advancement of science and math education, specifically through the use of modeling and simulation technologies. For more information, please visit www.shodor.org

Related Academic Standards

New York State

NY-6.EE.9 Use variables to represent two quantities in a real-world problem that change in relationship to one another. Given a verbal context and an equation, identify the dependent variable, in terms of the other quantity, thought of as the independent variable. Analyze the relationship between the dependent and independent variables using graphs and tables, and relate these to the equation.

NY-8.SP.1 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.

NY-8.SP.2 Understand 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.

NY-8.SP.3 Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept.

AI.S.ID.6 Represent bivariate data on a scatter plot, and describe how the variables’ values are related.

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