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.
You sold 43 adult tickets
1.
2.
<u> </u><u>Sub (1, -5) into equation to find '</u><em><u>b'</u></em><u />
3.
4.
4x+8y=40
0.8*8=6.4
4x+6.4=40
40-6.4=33.6
4x=33.6
33.6\4=8.4
X=8.4
Substitue y=3x into the other equation to get 3x=-x+4. Solve this to get 4x=4 therefore x=1.
knowing this, y=3
