In statistics, regression is a statistical process for evaluating the connections among variables. Simple linear regression is the technique for estimating how one variable of interest (the dependent variable) is affected by changes in another variable (the independent variable).
x and y are the variables. b = The slope of the regression line a = The intercept point of the regression line and the y axis. N = Number of values or elements X = First Score Y = Second Score ΣXY = Sum of the product of first and Second Scores ΣX = Sum of First Scores ΣY = Sum of Second Scores ΣX2 = Sum of square First Scores
To calculate the simple linear regression equation,
let consider the two variable as dependent (x) and the the independent variable (y).
X = 4, Y = 5
X = 6, Y = 8
You will get the slope as 1.5, y-intercept as -1 and the regression equation as -1 + 1.5x.