A .The probability that your team wins the championship give that
Answer:
Squared differences between actual and predicted y
Step-by-step explanation:
The least squares regression method used in predictive modeling for linear regression models produces a best fit line which will minimize the square of the mean difference between the actual and projected or predicted values of the dependent, y variable. Hence, the when the sum of the squared value of the difference between the actual and predicted values (residual) are taken, the fit which gives the minimum sum of squared value is the best fit line upon which the estimated regression equation is based.
Answer:
You forgot to show the picture or questions
Step-by-step explanation:
Answer:
The coordinates of the vertices of the image will be:
P'=(-3,-8)
Q'=(-6,4)
R'=(1,-1)
Step-by-step explanation:
If you reflect a point P=(x,y) across the x-axis, the coordinates of the image will be P'=(x,-y), then:
P=(-3,8)=(xp,yp)→xp=-3, yp=8→P'=(xp,-yp)→P'=(-3,-8)
Q=(-6,-4)=(xq,yq)→xq=-6, yq=-4→Q'=(xq,-yq)=(-6,-(-4))→Q'=(-6,4)
R=(1,1)=(xr,yr)→xr=1, yr=1→R'=(xr,-yr)→R'=(1,-1)
Answer (<u>assuming it can be in slope-intercept form)</u>:
y = -x - 1
Step-by-step explanation:
When knowing the slope of a line and its y-intercept, you can write an equation to represent it in slope-intercept form, or y = mx + b format. Substitute the m and b for real values.
1) First, find the slope of the equation, or m. Pick any two points from the line and substitute their x and y values into the slope formula, 
. I chose the points (0, -1) and (-1, 0):
Thus, the slope is -1.
2) Now, find the y-intercept, or b. The y-intercept of a line is the point at which the line crosses the y-axis. By reading the graph, we can see that the line intersects the y-axis at the point (0,-1), therefore that must be the y-intercept.
3) Now, substitute the found values into the y = mx + b formula. Substitute -1 for m and -1 for b:
