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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Answer:
y=3/-1x+4
Step-by-step explanation:
Okay so first thing you need to know is that if there is an ordered pair (x, y) where x is 0, your y-intercept is your y. For example, your problem has (0, 4) your x is 0 and your y is 4. Therefore your y-intercept is 4 which is the b. To find your mx, or slope, you need to do (y2-y1)/(x2-x1). Your y2 will be your y in your second ordered pair and your y1 will be in your y in the first ordered pair. Same for your x. So, (4-1)/(0-1) which equals 3/-1. 3/-1 is your slope. So, your answer in slop intercept form is: y= 3/-1x+4. You could also try y= -3x+4 if that makes you more comfortable.
I know this is long this is my first time doing this lol.
The number 2852.1 is already rounded to the tenth since the tenth place is one place to the right of the decimal
