STATISTICAL TECHNIQUES AND TOOLS
REGRESSION
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
Minimizing the sum of the squares of all values of the explanatory variable.
|
|
|
Minimizing the sum of the squares of all values of the response variable.
|
|
|
Minimizing the products of each value of the response variable and the predicted value based on the regression equation.
|
|
|
Minimizing the sum of the squares of the residuals.
|
Detailed explanation-1: -The least squares method is a statistical procedure to find the best fit for a set of data points by minimizing the sum of the offsets or residuals of points from the plotted curve. Least squares regression is used to predict the behavior of dependent variables.
Detailed explanation-2: -A least squares regression line represents the relationship between variables in a scatterplot. The procedure fits the line to the data points in a way that minimizes the sum of the squared vertical distances between the line and the points. It is also known as a line of best fit or a trend line.
Detailed explanation-3: -least squares means that some of the squares of the residuals are minimized. false. least squares means the sum of the squared residuals is minimized because in a least squares regression line, the sum of the squares of the residuals is minimized, not the individual residuals.