Answer:
d) Squared differences between actual and predicted Y values.
Step-by-step explanation:
Regression is called "least squares" regression line. The line takes the form = a + b*X where a and b are both constants. Value of Y and X is specific value of independent variable.Such formula could be used to generate values of given value X.
For example,
suppose a = 10 and b = 7. If X is 10, then predicted value for Y of 45 (from 10 + 5*7). It turns out that with any two variables X and Y. In other words, there exists one formula that will produce the best, or most accurate predictions for Y given X. Any other equation would not fit as well and would predict Y with more error. That equation is called the least squares regression equation.
It minimize the squared difference between actual and predicted value.
Answer:
16 dimes
Step-by-step explanation:
He already has 7, and got 9 more, so we can add 7 and 9
7+9 =16
So, Dan has 16 dimes now
Hope this helps! :)
You will need to set equations to solve for x and y coordinate.
(2+x)/2=4
2+x=8
x=6
(6+y)/2=10
6+y=20
y=14
The answer is A. (6,14)
Answer:
$125
Step-by-step explanation:
11,000 - 9,500 = 1,500
1,500 / 12 = 125 (we use 12 because 12 months = 1 year)
Answer: 9
Step-by-step explanation: 9 x 9 equals 81 and 81 add 9 is 90