Answer:
looks like B-cant really see the numbers
Step-by-step explanation:
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.
1) the slope of the line is where x=0 and the y coordinate is 1
2) plant 2 of the coordinate pairs on the graph, then from there find where the y intercept passes through where x=0
3) slope form is y=mx+b
y=-3x+9 if you use (-3,9)
plant it on the graph and then write a brief explanation
The answer is for question 12, x = -9.3333333
