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+# A shiny app for exploring regression relations on mtcars data
+
+## Introduction
+
+This app creates custom regression model for **mtcars** dataset.
+
+The user can choose one of the following workflows.
+
+1.  The user can choose the **Select best model** option. In that case,
+    the user may choose the number of variables to be selected for the
+    model. The code will use adjusted R squared value to choose the best
+    model restricted by the number of variables.
+
+2.  The user can create the model by choosing the variables to be used.
+    The best model will be chosen from the set of all possible models
+    that these variables can generate.
+
+The options to choose the variables are given in the left panel. The
+residual statistics are also generated.
+
+## Packages used
+
+1.  shiny
+2.  shinyjs
+3.  leaps
+4.  dplyr
+5.  ggplot2
+6.  gridExtra
+7.  grid
+
+## Residual diagnostics
+
+A sample of residual statistics is given below. The diagnostic plot
+includes
+
+1.  Residual vs Fitted Plot
+2.  Normal Q-Q plot
+3.  Scale-Location plot
+4.  Cook’s distance
+5.  Residual vs Leverage Plot
+6.  Cook’s distance vs Leverage
+    *h*<sub>*i**i*</sub>/(1−*h*<sub>*i**i*</sub>)
+
+![Residual diagnostics](Residual_diag.PNG)
+
+## Reference
+
+1.  [Playing with ggplot2](https://rpubs.com/therimalaya/43190) by Raju
+    Rimal
+2.  Weisberg, S., 2005. [Applied linear
+    regression](http://www.ru.ac.bd/wp-content/uploads/sites/25/2019/03/304_03_Weisberg-Applied-Linear-Regression-Wiley-2013.pdf)
+    (Vol. 528). John Wiley & Sons.
+3.  [Shiny](https://cran.r-project.org/web/packages/shiny/index.html)
+4.  [leaps: Regression Subset
+    Selection](https://cran.r-project.org/web/packages/leaps/leaps.pdf)