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:
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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