Use sample data or upload a file


The app takes a few seconds to load. Please wait for ~12 seconds.



Upload Data

Upload data from a comma or tab separated file.






Upload Data

Upload data from a .xls or .xlsx file.












Upload Data

Upload data from a .json file.
















Upload Data

Upload data from a .dta file.
















Upload Data

Upload data from a .sav file.
















Upload Data

Upload data from a .sas7bdat file.















Click on a sample for more information





Select Data Set

Select a data set from the drop down box and click on submit.



Data Transformation

Rename variables and modify data types.


Variable
Rename Variable
Modify Data Type




Select Variables

Click on Yes to select variables.


Do you want to select variables?



Filter Data

Click on Yes to filter data.


Do you want to filter data?



Data Screening

Screen data for missing values, verify variable names and data types.



                    

Sample Data

Click on Yes to create a random sample of data.


Draw a random sample of the data?







Partition Data

Click on Yes to partition data into training and test set.


Do you want to partition data into training set and testing set?






What do you want to do?




Regression



Residual Diagnostics



Heteroskedasticity Tests



Collinearity Diagnostics



Measures of Influence



Model Fit Assessment



Variable Contribution

Multiple Linear Regression

Ordinary least squares regression.



Model Formula:





                    


Select Procedure:




Breusch Pagan Test

Test for constant variance. It assumes that the error terms are normally distributed.



Model Formula:

Use previous model:


Fitted Values:

p Value Adjustment:

RHS:

Variables:

Multiple:




                                

Bartlett Test

Test if k samples have equal variances.


Variables:




                                            

Variable:

Grouping Variable:




                                            

Model Formula:




                                            

F Test

Test for heteroskedasticity under the assumption that the errors are independent and identically distributed (i.i.d.).



Model Formula:

Use previous model:


Variables:

Fitted Values:

RHS:




                                

Score Test

Test for heteroskedasticity under the assumption that the errors are independent and identically distributed (i.i.d.).



Model Formula:

Use previous model:


Variables:

Fitted Values:

RHS:




                                

Collinearity Diagnostics

Variance inflation factor, tolerance, eigenvalues and condition indices.



Model Formula:

Use previous model:





                    

Select Procedure:





Select Procedure:



Added Variable Plot

Added variable plot provides information about the marginal importance of a predictor variable, given the other predictor variables already in the model. It shows the marginal importance of the variable in reducing the residual variability.



Model Formula:

Use previous model:





                                


Residual Plus Component Plot

The residual plus component plot indicates whether any non-linearity is present in the relationship between response and predictor variables and can suggest possible transformations for linearizing the data.



Model Formula:

Use previous model:





Residual vs Regressor Plot

Graph to determine whether we should add a new predictor to the model already containing other predictors. The residuals from the model is regressed on the new predictor and if the plot shows non random pattern, you should consider adding the new predictor to the model.



Model Formula:

Select Regressor:

Use previous model:










Thank you for using olsrr !

Now you should close this window.