computing residuals\nthe line of best fit to model the data in the table is y = 5.2x - 0.4.\nwhat is the…

computing residuals\nthe line of best fit to model the data in the table is y = 5.2x - 0.4.\nwhat is the residual for 5?\n-1.6\n-0.6\n0.6\n1.6\nx y\n1 8\n2 13\n3 18\n4 23\n5 24

computing residuals\nthe line of best fit to model the data in the table is y = 5.2x - 0.4.\nwhat is the residual for 5?\n-1.6\n-0.6\n0.6\n1.6\nx y\n1 8\n2 13\n3 18\n4 23\n5 24

Answer

Explanation:

Step1: Predict y - value for x = 5

Substitute x = 5 into y = 5.2x−0.4. $y_{predicted}=5.2\times5 - 0.4=26 - 0.4 = 25.6$

Step2: Calculate the residual

Residual = $y_{actual}-y_{predicted}$. Here, $y_{actual}=24$ when x = 5. Residual = $24 - 25.6=-1.6$

Answer:

-1.6