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.

5 0

3 years ago

Read 2 more answers

∠45° is complementary to which of the following angles?

mixas84 [53]

Answer:

45°

Step-by-step explanation:

complementary angles add up to 90° so it's 90-45

4 0

2 years ago

A certain type of bacteria doubles in population every 6 hours. There were approximately 100 bacteria at the beginning of the da

Zepler [3.9K]

Answer:

1600 after 24 hours

Step-by-step explanation:

100+100 = 200 after 6 hours

200+200 = 400 after 12 hours

400+400 = 800 after 18 hours

800+800 = 1600 after 24 hours

5 0

3 years ago