![]() For example, if you wanted to generate a line of best fit for the association between height, weight and shoe size, allowing you to predict shoe size on the basis of a person's height and weight, then height and weight would be your independent variables ( X 1 and X 1) and shoe size your dependent variable ( Y). This regression equation calculator with steps will provide you with all the calculations. Step 2: Type in the data or you can paste it if you already have in Excel format for example. ![]() Now, here we need to find the value of the slope of the line, b, plotted in scatter plot and. The steps to conduct a regression analysis are: Step 1: Get the data for the dependent and independent variable in column format. The equation of linear regression is similar to the slope formula what we have learned before in earlier classes such as linear equations in two variables. To begin, you need to add data into the three text boxes immediately below (either one value per line or as a comma delimited list), with your independent variables in the two X Values boxes and your dependent variable in the Y Values box. Linear regression shows the linear relationship between two variables. The case of one explanatory variable is called simple linear regression for more than one, the process is called multiple. This calculator will determine the values of b 1, b 2 and a for a set of data comprising three variables, and estimate the value of Y for any specified values of X 1 and X 2. In statistics, linear regression is a statistical model which estimates the linear relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables ). The line of best fit is described by the equation ลท = b 1X 1 + b 2X 2 + a, where b 1 and b 2 are coefficients that define the slope of the line and a is the intercept (i.e., the value of Y when X = 0). The easy-to-use simple linear regression calculator gives you step-by-step solutions to the estimated regression equation, coefficient of determination and. This simple multiple linear regression calculator uses the least squares method to find the line of best fit for data comprising two independent X values and one dependent Y value, allowing you to estimate the value of a dependent variable ( Y) from two given independent (or explanatory) variables ( X 1 and X 2).
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