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:
To plot point A, you would count over to the left six places on the x-axis. Then, count up two places on the y-axis.
Answer:
4z + 5
Step-by-step explanation:
16 and 20 are both dividable by 4, so you divide them both by four and then you have your answer
Check the picture below.
for "b", well, recall that the sum of all interior angles in a triangle is 180°.
for "a", "c" and "d", well, all those are just <u>intercepted arcs</u>.