Answer: D. minimizes the sum of the squared residuals
Step-by-step explanation: The ordinary least square method is often used in locating the trendine which best fits a graphical linear model. The best is one in which the sum of the squared residual is smallest. The residual refers to the difference between the actual and the predicted points. The sum of the squared differences is obtained and the trend line is positioned where the residual is minimum. Choosing a OLS, and minimizing the sum.of the squared residual, the error difference between the predicted and actual score is minimized or reduced, hence, improving the prediction accuracy of our model.
Let me see if I understand your question:
101=50-h
this would just be an equation with a variable: this variable is "h". Variable is an unknown value, like a name for "something".
so we could say that 101 equals 50 minus "something" and we call this something "h"
this is what 101=50-h "means"
as it happens, we can find out the value of this h:
we can subtract 50 from both sides of the equation:
101-50=50-50-h
51=-h
and multiply by (-1)
-51=h
so our h is equal to -51.
so... does not actually mean here 49...
let me know if you have further questions!
Answer:
Question 2: 4th answer, Question 3: 3rd answer
Step-by-step explanation:
I think that is correct hope it helps!
