# Multiple Linear Regression Calculator

Instructions: You can use this Multiple Linear Regression Calculator to estimate a linear model by providing the sample values for several predictors $$(X_i)$$ and one dependent variable $$(Y)$$, by using the form below: Y values (comma or space separated) = X values (comma or space separated, press '\' for a new variable) Name of the dependent variable (Optional) Name of the independent variables (Comma separated. Optional)

#### Multiple Linear Regression Calculator

More about this Multiple Linear Regression Calculator so you can have a deeper perspective of the results that will be provided by this calculator. Multiple Linear Regression is very similar to Simple Linear Regression, only that two or more predictors $$X_1$$, $$X_2$$, ..., $$X_n$$ are used to predict a dependent variable $$Y$$. The multiple linear regression model is

$Y = \displaystyle \beta_0 + \beta_1 X_1 + \beta_2 X_2 + ... + \beta_n X_n + \epsilon$

where $$\epsilon$$ is the error term that has the property of being normally distributed with mean 0 and constant variance $$\epsilon ~ N(0, \sigma^2)$$. After providing sample values for the predictors $$X_1$$, $$X_2$$, ..., $$X_n$$ and the response variable $$Y$$, estimates of the population slope coefficients are obtained by minimizing the total sum of squared errors. The estimated model is expressed as:

The expression that is used to compute the odds for the occurrence of an event, $$p$$, given its probability is shown below:

$\hat Y = \displaystyle \hat\beta_0 + \hat\beta_1 X_1 + \hat\beta_2 X_2 + ... + \hat\beta_n X_n$

If, on the other hand, you want to use only one predictors, you can use this simple linear regression calculator instead.

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