In 8th grade, students created scatter plots Students can represent data on a scatter plot using an appropriate scale and describe the relationship between two and described patterns of association between quantitative variables. two quantities. They also informally fit a Represent the data from the table below in a Example: straight line to data based on how closely the scatter plot. Determine if and what the relationship is data points resembled a line. That knowledge between the population of each high school and the number is extended to fitting a linear regression of active band members. equation to a set of data using technology. Technology includes graphing calculators, computer software/programs and web-based applets and tools. The initial exploration with technology should include a discussion of domain and Example: The data gives the number of miles driven and advertised price for 11 used models of a particular car. and their relationship to the graphing Use a calculator or graphing technology to make a scatter plot of the data. window. Most technology tools include an the correlation coefficient for the data above. Describe what the automatic feature that graphs data within a correlation coefficient means in regards to the data. window representative of the data, however Fit a linear function to the relationship between miles driven and the understanding of the graphing window can price of these cars. lead to further discussions about domain, do you know that this is the best-fit range, interpolation and extrapolation. If a used car is driven 98,000 miles, what will the price be (to the nearest dollar)? If the price of the car is $12,540, how many miles could have been driven (to the nearest thousand)? Instructional Resources Additional Resources (Illustrative Mathematics) (Illustrative Mathematics) Back to: Interpreting Categorical and Quantitative Data NC.M1.S-ID.6b Summarize, represent, and interpret data on two categorical and quantitative variables. Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
In 8th grade, students created scatter plots and described patterns of association between two quantities. They also informally fit a straight line to data based on how closely the data points resembled a line. That knowledge is extended to fitting a linear regression equation to a set of data using technology. Technology includes graphing calculators, computer software/programs and web-based applets and tools. The initial exploration with technology should include a discussion of domain and and their relationship to the graphing window. Most technology tools include an automatic feature that graphs data within a window representative of the data, however understanding of the graphing window can lead to further discussions about domain, range, interpolation and extrapolation. Students can represent data on a scatter plot using an appropriate scale and describe the relationship between two quantitative variables. Example: Represent the data from the table below in a scatter plot. Determine if and what the relationship is between the population of each high school and the number of active band members. Example: The data gives the number of miles driven and advertised price for 11 used models of a particular car. Use a calculator or graphing technology to make a scatter plot of the data. the correlation coefficient for the data above. Describe what the correlation coefficient means in regards to the data. Fit a linear function to the relationship between miles driven and the price of these cars. do you know that this is the best-fit If a used car is driven 98,000 miles, what will the price be (to the nearest dollar)? If the price of the car is $12,540, how many miles could have been driven (to the nearest thousand)? Instructional Resources Additional Resources (Illustrative Mathematics) (Illustrative Mathematics) Back to: Interpreting Categorical and Quantitative Data NC.M1.S-ID.6b Summarize, represent, and interpret data on two categorical and quantitative variables. Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.