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Subject

Math, Science & Technology

Virtual Manipulative

Click here for this interactive resource.

Content Provider

The National Library of Virtual Manipulatives is a three-year NSF supported project to develop a library of uniquely interactive, web-based virtual manipulatives or concept tutorials, mostly in the form of Java applets, for mathematics instruction (K-8 emphasis). The project includes dissemination and extensive internal and external evaluation. For more information, please visit http://nlvm.usu.edu/en/nav/vlibrary.html.

Description

This interactive web-based resource allows students to create scatterplots. The scatterplot creates the line of best fit and finds its equation. There is also an activity for students to help them practice their scatter-plotting skills.

Credits

Principal Investigators
Larry Cannon
Jim Dorward
Bob Heal
Leo Edwards

Java Applet Programming
Ethy Cannon
Joel Duffin
David Stowell
Zeke Susman
Richard Wellman
Jennifer Youngberg

Web Site Programming
Joel Duffin

Related Academic Standards

New York State

6.EE.9 Use variables to represent two quantities in a real-world problem that change in relationship to one another; write an equation to express one quantity, thought of as 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. For example, in a problem involving motion at constant speed, list and graph ordered pairs of distances and times, and write the equation d = 65t to represent the relationship between distance and time.

8.SP.2 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.

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. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height.

S-ID.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

S-ID.6.b Informally assess the fit of a function by plotting and analyzing residuals.

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