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.
What Question Are You Asking Here?
Answer:
The measure of an inscribed angle is half the measure of the intercepted arc
∠EFG creates Arc EDG
if ∠EFG is 1/2 arc EDG then 115° x 2 = 230°
A circle is 360°.
The remaining arc EFG is 360° - 230° = 130°
∠EDG is 1/2 of arc EFG so, 130° ÷ 2 = 65°
∠EDG = 65°
Answer:
A lurking variable is a variable that has an important effect on the relationship among the variables in the study, but is not one of the explanatory variables studied. Two variables are confounded when their effects on a response variable cannot be distinguished from each other.
The average speed of his trip is = 12 mile/ hour
The total distance covered by the driver = 240 miles
The rate at which he traveled = 12 miles per hour
Therefore, the time he used to cover his distance
= 240/12
= 20 hrs
But average speed = distance/ time
= 240/ 20
= 12 miles/ hour
Therefore, the average speed of his trip is = 12 mile/ hour
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brainly.com/question/11753352
