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.
You add all those number together then divide the number you got by how many numbers there are and that's your answer, 61.1
edit : dont listen to me I didnt see the numbers 64 and 65, im sorry
Answer:
C and E
Step-by-step explanation:
To answer this question, we plug in the X values of the coordinates into the equation to see if they'll give us the corresponding Y value.
(X, Y)
Example:
Y = 5X
6 != 5 * 3
We do this for every coordinate point. If the problem doesn't make sense, it doesn't fall on the line. Let's test every one of these.
B. (0, 1)
1 != 5 * 0
C. (3, 15)
15 = 5 * 3
D. (4, 2)
2 != 5 * 4
E. (-1, -5)
-5 = 5 * -1
F. (-1, 5)
5 != 5 * -1
* For those who don't know, the != is how to say "not equal to" in computer science.
Answer:
the third one
Step-by-step explanation:
1/3 = 10/30
1/5 = 6/30
1/2 = 15/30
10+6+15= 31/30
31/30 = 1 1/30
It would be Less Than 1 1/2 Gallons
