Stats.Blue

# Multiple Linear Regression Calculator

• Values of the response variable $y$ vary according to a normal distribution with standard deviation $\sigma$ for any values of the explanatory variables $x_1, x_2,\ldots,x_k.$ The quantity $\sigma$ is an unknown parameter.

• Repeated values of $y$ are independent of one another.

• The relationship between the mean response of $y$ (denoted as $\mu_y$) and explanatory variables $x_1, x_2,\ldots,x_k$ is linear and is given by $\mu_y=\beta_0+\beta_1 x_1+\cdots +\beta_k x_k$ where each $\beta_i$ is an unknown parameter.
 Resp. Var. $y$ Expl. Var. $x_1$ Expl. Var. $x_2$ Variable Names (optional): Sample data goes here (enter numbers in columns):

 Model: $y=\beta_0 + \beta_1 x_1 +\beta_2 x_2$

Display output to

 Include Interaction $x_1$*$x_1$ $x_1$*$x_2$ $x_2$*$x_2$

Summary of Overall Fit

Analysis of Variance Table

 Source df SS MS $F$-statistic $p$-value Regression Residual Error Total

 Histogram of the Residuals Percent Residuals

 Normal Probability Plot of Residuals Residual Quantiles Standard Normal Quantiles

Five Number Summary of Residuals

 Minimum: 1st Quartile: Median: 3rd Quartile: Maximum: