Explain what each point on the least-squares regression line represents.
A) Each point on the least-squares regression line represents the y-value of the data set at that corresponding value of x.
B) Each point on the least-squares regression line represents the predicted y-value at the corresponding value of x.
C) Each point on the least-squares regression line represents the y-values that would be considered ideal at that corresponding value of x.
D) Each point on the least-squares regression line represents one of the points in the data set.
Regression Analysis is one of the statistical method that helps to identify the cause and effect relationship between two variables. It is a statistical procedure developed to determine whether two or more interval or ratio level variables are related and whether the change in one variable is related in any way to movement in the other or others. It allows decision maker to determine how different values of one variable (dependent variable) might or might not help to explain variation in another variable (independent variable).
Y = a + bX
- Y = the value of Y calculated from the estimated regression equation.
- a = the point on Y where the regression line intercepts on Y
- b = the amount of change in X required for a corresponding change in Y which when plotted represents the slope of the line.
- X = a measured value for X.