Lesson plan

Determine an equation for linear regression by using a least-squares regression model

teaches Common Core State Standards CCSS.Math.Content.HSN-Q.A.1 http://corestandards.org/Math/Content/HSN/Q/A/1
teaches Common Core State Standards CCSS.Math.Content.HSS-ID.B.6c http://corestandards.org/Math/Content/HSS/ID/B/6/c
teaches Common Core State Standards CCSS.Math.Content.HSS-ID.C.7 http://corestandards.org/Math/Content/HSS/ID/C/7
teaches Common Core State Standards CCSS.Math.Practice.MP4 http://corestandards.org/Math/Practice/MP4
teaches Common Core State Standards CCSS.Math.Practice.MP6 http://corestandards.org/Math/Practice/MP6

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Big Ideas: We can identify the linear equation that best fits the relationship between two variables by finding the least-squares regression line (LSRL). We should interpret the slope and y-intercept of the LSRL in context of the data. This lesson builds on students’ previous work in high school statistics with bivariate data and scatterplots. The task will ask students to create two quantitative data sets by measuring their hands and counting the number of candies they can count. Students will then use technology to solve for the LSRL. Using the slope and y-intercept from the LSRL model, students should then interpret these values in context of the data. Vocabulary: quantitative, explanatory variable (independent variable), response variable (dependent variable), bivariate, regression, least-squares regression line, slope, y-intercept, association Special Materials: Large bowl / container 2-3 bags of candies (chewy chocolate taffy candies, square fruit-flavored soft taffy candies, or peppermints)