Notice the picture below
the lateral area, or just the area of the sides, well, the sides are really just 4 triangles, so just get the area of each, and sum them up, that's the lateral area
Minimizing the sum of the squared deviations around the line is called Least square estimation.
It is given that the sum of squares is around the line.
Least squares estimations minimize the sum of squared deviations around the estimated regression function. It is between observed data, on the one hand, and their expected values on the other. This is called least squares estimation because it gives the least value for the sum of squared errors. Finding the best estimates of the coefficients is often called “fitting” the model to the data, or sometimes “learning” or “training” the model.
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Answer:
m = 3/40
Step-by-step explanation:
4 = 3/4m - 6
m*4 = m(3/4m -6)
4m = m*3/4m + m*-6
4m = 3/4 - 6m
6m + 4m = 3/4
10m = 3/4
m = (3/4)/10
m = 3/40
check:
4 = 3/(4*3/40) - 6
4 = 3/(12/40) - 6
4 = (3*40)/12 - 6
4 = 120/12 - 6
4 = 10 - 6