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:
91.125 cm3
Step-by-step explanation:
i took the test
Answer:
a) both have same distance
b) second park has a larger area
Step-by-step explanation:
a) park a: circumference is
75+75+30+ pi*30( the diameter of the inward semi circle is 30)
be also has the same perimeter because the diameter of outward semi circle is also 30
b) in the first park, the semi circle area is cut out
in the second its part of the park