What Is Y in Linear Regression?

Linear regression is a way to model the relationship between two variables. The equation has the form Y= a + bX, where Y is the dependent variable (that’s the variable that goes on the Y axis), X is the independent variable (i.e. it is plotted on the X axis), b is the slope of the line and a is the y-intercept.

What is Y in statistics?

“Y” because y is the outcome or dependent variable in the model equation, and a “hat” symbol (circumflex) placed over the variable name is the statistical designation of an estimated value.

The intercept (often labeled the constant) is the expected mean value of Y when all X=0. Start with a regression equation with one predictor, X. If X sometimes equals 0, the intercept is simply the expected mean value of Y at that value. If X never equals 0, then the intercept has no intrinsic meaning.

What does Y mean in least squares regression line?

y is the dependent variable, such as the estimated or expected total cost of electricity during a month. The amount of y is dependent upon the amounts of a and bx.

The slope and y-intercept values indicate characteristics of the relationship between the two variables x and y. The slope indicates the rate of change in y per unit change in x. The y-intercept indicates the y-value when the x-value is 0.