Answer:
yes, i think it is
Step-by-step explanation:
Answer:
B) The sum of the squared residuals
Step-by-step explanation:
Least Square Regression Line is drawn through a bivariate data(Data in two variables) plotted on a graph to explain the relation between the explanatory variable(x) and the response variable(y).
Not all the points will lie on the Least Square Regression Line in all cases. Some points will be above line and some points will be below the line. The vertical distance between the points and the line is known as residual. Since, some points are above the line and some are below, the sum of residuals is always zero for a Least Square Regression Line.
Since, we want to minimize the overall error(residual) so that our line is as close to the points as possible, considering the sum of residuals wont be helpful as it will always be zero. So we square the residuals first and them sum them. This always gives a positive value. The Least Square Regression Line minimizes this sum of residuals and the result is a line of Best Fit for the bivariate data.
Therefore, option B gives the correct answer.
Answer:
The area of the clock 
Step-by-step explanation:
We have been given the face of the clock that is 
So that is also the circumference of the clock.
Since the clock is circular in shape.
So 
From here we will calculate the value of radius 
of the clock that is circular in shape.
Then 
Now to find the area of the clock we will put this value of (r) in the equation of area of the circle.
Now 
So the area of the face of the clock =
Hello,
Answer A
d :the distance in miles
t: the time in hours
v: the speed in miles/hours (vistesse)
d=v*t
==>d=40*4=160(mi)
d=55*x=160==>x=160/55=2.909090... (mi/(mi/h)=h)≈2.91(hours)
Answer: C. Industrialization
Step-by-step explanation:
