Below the plot, you can find the linear regression equation for your data. We will show you the scatter plot of your data with the regression line. The calculator needs at least 3 points to fit the linear regression model to your data points. 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). To use the linear regression calculator, follow the steps below: Enter your data, up to 30 points. If you want to find the x-intercept, give our slope. The magic lies in the way of working out the parameters a and b. As you can see, the least square regression line equation is no different from linear dependencys standard expression. 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. The formula for the line of the best fit with least squares estimation is then: y a 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. Effect size: Leave empty if you know the effect type and the effect. Predictors The number of independent varaibles (X). : Significant level (0-1), maximum chance allowed rejecting H0 while H0 is correct (Type1 Error) n: The sample size. 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). Video Statistical Power Information Power Calcualtors Regression Sample Size. It can serve as a slope of regression line calculator, measuring the relationship between the two factors. ![]() This page includes a regression equation calculator, which will generate the parameters of the line for your analysis. 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). The linear regression calculator will estimate the slope and intercept of a trendline that is the best fit with your data.
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