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Your task this week is to make up data for 12 imaginary ten-year old boys, enter that data and compose a scatterplot (with trendline), compute a least-squares line and determine the correlation coeffi

by | Nov 28, 2023 | math

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Your task this week is to make up data for 12 imaginary ten-year old boys, enter that data and compose a scatterplot (with trendline), compute a least-squares line and determine the correlation coefficient.   Note that ten-year old boys range in height between 42 and 62 inches.  Weights are typically between 60 and 90 pounds.

Required elements:

  • Scatterplot showing WEIGHT on the vertical (y) axis
  • Equation of Best-fit line (e.g. Weight = 40.5 + 2.5 (height)
  • R^2 value
  • R (correlation) – this is just the square root of the R^2.

You may use any technology you like.  I suggest using either Excel or an online regression calculator like https://keisan.casio.com/exec/system/14059929550941 or https://www.graphpad.com/quickcalcs/linear1/

Upload your scatterplot and regression output using the picture tool, then answer the following questions:

  • What does the correlation say about the relationship between the height and weight
  • Describe a real-world scenario where you might use least-squares regression to describe a relationship or make a prediction.
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