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.
Note
Write the number until underlined point.I did it till end
Answer:
30
Step-by-step explanation:
Original Equation: 2(7 + 8)
So you have to multiply 2 by 7 which equals 14
Then you multiply 2 by 8 which equals 16
Your equation should now look like this: 14 + 16
Add 14 and 16 together.
Your answer is 30
Hope I helped :)
Please condsider brainliest
The correct answer is 3/8
Rewriting our equation with parts separated
1+7/8−6/4
Solving the fraction parts
7/8 - 6/4?
Find the LCD of 7/8 and 6/4 and rewrite to solve with the equivalent fractions.
LCD = 8
7/8−1 2/8=−58
7
8
−
12
8
=
−
5
8
Combining the whole and fraction parts
1−5/8=3/8
