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This is the first version of the 2-31 eTool, the one described in the textbook. It can help students get a visual of the LSRL. The next activity in the list explores the same ideas as this one (plus a few additional ones) and may be a better choice if you have some flexibility.

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A least squares regression line (LSRL) is a line of best fit that minimizes the sum of the square of the residuals. For additional information, see the Math Notes box in Lesson 6.2.1 and the narrative in Checkpoint 8 at the back of the textbook.

This is a one-page activity that contains an eTool to demonstrate the LSRL as the line that minimizes the area of the squares drawn on the residuals, using the basketball data provided. It follows along with problem 2-31 from lesson 2.1.4 of the CPM AP Statistics textbook.

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Lawrence Semiconductor Research Laboratory (LSRL) is a company that provides epitaxial services for the semiconductor industry. It offers epitaxial growth, characterization, and operations solutions for silicon photonics, si-based power devices, virtual …

The LSRL, or Least Squares Regression Line, is a method used in statistics to find the best-fitting line through a set of data points on a scatterplot. This line minimizes the sum of the squares of the vertical distances (residuals) from each data point to the line itself, helping to make predictions about one variable based on another.

Using Desmos to find LSRL with CPM3 Likes