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The value of 4 in 47,163 is 10 times greater than the value of 4 in 34,258.
Each time you move one place over (e.g. tens to hundreds) the number gets 10 times larger if you move to the left and 10 times smaller if you move to the right. So, for example you go from tens to hundreds it is 10 times larger, but if you go from hundreds to tens then it is 10 times smaller.
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.
To learn more about regression visit: brainly.com/question/14563186
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13% of the time yet it is a great day
Answer:
o< 1/16x + 9/16
Step-by-step explanation:
x+9>16o
Flip the equation.
16o<x+9
Divide both sides by 16.
16o/16 < x+9/16
o< 1/16x + 9/16
