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Relationships between Two Quantitative Variables: Linear Models & Correlation (Common Core Aligned Lesson)
This product includes a lesson plan with worksheet and answer key aligned with the common core. Students review how represent the relationship between two quantitative variables on a scatterplot. Students learn how to fit and interpret linear models; how to compute and interpret the correlation coefficient of a linear fit; how to interpret, plot, and analyze residuals; and how to distinguish between correlation and causation. The worksheet can be used as an in-class handout or as homework. Questions assess statistical reasoning as well as mechanics.
This lesson reviews linear functions and correlation and further emphasizes evaluating the fit of a linear model. A complete lesson on functions (linear, quadratic, and exponential) that describe the relationship between two quantitative variables can be found here.
This product includes:
1) Lesson lecture slides in PDF (annotated with speaker notes) and PowerPoint
2) Lesson lecture handout in PDF
3) Worksheet in PDF
4) Answer key with and without detailed rubric in PDF
5) A bonus 15-term vocabulary list relevant to Common Core Standards: Summarize, represent, and interpret data on two quantitative variables (HSS.ID.B.6, HSS.ID.B.6.A, HSS.ID.B.6.B, HSS.ID.B.6.C); and interpret linear models (HSS.ID.C.7, HSS.ID.C.8, HSS.ID.C.9) in PDF
1) Review how to represent two quantitative variables on a scatterplot and describe the relationship.
2) Learn how to fit a linear function and interpret the linear model.
3) Learn how to compute and interpret the correlation coefficient of a linear fit.
4) Learn how to interpret, plot, and analyze residuals.
5) Learn how to distinguish between correlation and causation.
Common Core Standards:
HSS.ID.B.6: Represent two quantitative variables on a scatterplot and describe how the variables are related.
HSS.ID.B.6.A: Fit a function to the data; use functions fitted to data to solve problems in the context of data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models.
HSS.ID.B.6.B: Informally assess the fit of a function by plotting and analyzing residuals.
HSS.ID.B.6.C: Fit a linear function for a scatterplot that suggests a linear association.
HSS.ID.C.7: Interpret the slope (rate of change) and intercept (constant term) of a linear model in the context of data.
HSS.ID.C.8: Compute (using technology) and interpret the correlation coefficient of a linear fit.
HSS.ID.C.9: Distinguish between correlation and causation.
About this product:
The materials in this product have been compressed into a *.zip file. Software to unzip the file is necessary to use these materials. The materials are unzipped into seven separate files. Software for reading PDF(*.pdf) or PowerPoint (*.pptx) documents is needed to use the respective file types.
This purchase is to be used by one teacher only for classroom use. These materials may not be shared without purchasing the appropriate number of licenses. These materials may not be uploaded to the internet in any form (classroom websites, personal websites, or network drives, etc.).
The data and plots were simulated and created, respectively, using R Statistical Software, a free open-source software for statistical computing. Please let me know if you are interested in educational products on using R for the Common Core.
Want more resources on statistics for the common core? Check these out!:
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© Statistics Education Resources, 2018
The National Governors Association Center for Best Practices and Council of Chief State School Officers are the sole owners and developers of the Common Core State Standards. © Copyright 2010. National Governors Association Center for Best Practices and Council of Chief State School Officers. All rights reserved.
This product is the work of Statistics Education Resources. Claims of alignment with the Common Core State Standards are the personal opinion of Statistics Education Resources and do not necessarily reflect the official views of the National Governors Association Center for Best Practices and Council of Chief State School Officers. No association with or endorsement by the National Governors Association Center for Best Practices and Council of Chief State School Officers is intended or implied.