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.
Well if she added three blue and four red originally, and is now using 16 red then we would divide 16 by the original four. Which means to get the number of blue we are gonna end up multiplying by four. So three times four is twelve. Which means she would use 12 blue and 16 red to get the same color she got with 3 blue and 4 red earlier. The equation, lets use x for blue and y for red, would be 4(3x + 4y) = desired color
Answer:
the shape is semetrical
Step-by-step explanation:
Answer:
D.pi
Step-by-step explanation:
Because it’s pi