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:
60.2 m
Step-by-step explanation:
Let x represent the width of the river. The distance from the point across from the tree to the second point is 15 m. The angle from this point to the tree across the river is 76°.
This makes the side opposite the angle x, the width of the river. It also means the 15 m side is adjacent to this angle.
The ratio opposite/adjacent is the ratio for tangent; this gives us the equation
x/15 = tan(76)
Multiply both sides by 15:
15(x/15) = 15(tan(76))
x = 15(tan(76)) ≈ 60.2
Your answer is 25% <span> of change in the price of a radio</span>
= 3 × 10-11
(scientific notation)
= 3e-11
(scientific e notation)
= 30 × 10-^12
(engineering notation)
(trillionth; prefix pico- (p))
= 0.0000000000
<span>(real number)</span>
