It's the reflexive property because it's just relating it to itself (def. of reflexive)
As we all know: A=A, B=B, mx=mx, nothing changes.
So the answer is D
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:
y=-5,x=2
Step-by-step explanation:
3x+3y=-9________________eqn 1
3x-3y=21________________eqn 2
using elimination method
3x+3y=-9
-
3x-3y=21
subtract equation 2 from equation 1
0+6y=-30
6y=-30
y=-30/6
y=-5
substitute the value of y in equation 1
3x+3y=-9
3x+3(-5)=-9
3x-15=-9
3x=-9+15
3x=6
x=6/3
x=2
Answer:
x=145°
Step-by-step explanation:
180 = 35 + x
x = 180-35
x= 145°
Eighty four divided by 6 is 14
