Multiple Linear Regression Calculator

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An online calculator to model data using multiple linear regression based on the ordinary least squares (OLS) regression method to estimate the relationship between a dependent variable \( y \) and several independent variables \( x_1, x_2 , ..., x_n \), given data values of all these variables, is presented.
The model used is of the form \[ \hat y = \hat \beta_0 + \hat \beta_1 x_1 + \hat \beta_2 x_2 + ..... + \hat \beta_n x_n \] is suggested.

The calculator gives the coefficients \( \beta_1 , \beta_2 , ......, \beta_0 \), the coefficient of determination R2 and the sum of squares errors defined below:

\( SST = \Sigma (y_i - \bar y)^2 \)
\( SSR = \Sigma (\hat y_i - \bar y)^2 \)
\( SSE = \Sigma (y_i - \hat y_i)^2 \)


Use of the Multiple Linear Regression Calculator

Note that The calculator does not give an answer if the number of rows \( m \) is smaller than the number of columns \( n \).
Enter the number of rows \( m \) and columns \( n \).
Values of the independent variables \( x_1, x_2 , ..., x_n \) and the depenedent variable \( y \) may be generated randomly or entered manually but must be updated.
Number of Rows: \( m = \)          Number of Variables: \( n = \)

Click here to enter \( m \) and \( n \) and generate a random matrix

Number of Decimals: \( m = \)


Change values of cells above (if needed) and click here



Output






More References and links

  1. multiple linear regression
  2. Coefficient of Determination