Check if your data follows a normal distribution with this web app!
Install the Shiny R package on your machine with the following command:
install.packages("shiny")
Once finished installing, clone or download this repository and open the "app.R" file with Rstudio. Rstudio will automatically detect that it is a Shiny app file and a "Run App" button will appear on the top of the editor screen. Click the button to run the app.
Alternatively, with the repository cloned, open your R console and set the working directory to the absolute path where the repository was cloned:
setwd(path_to_cloned_repository)
Then, load the Shiny library and run the file "app.R":
library(shiny)
runApp("app/app.R")
The app will start on a new browser tab in your default browser.
- Select any file to be input to the application by browsing the file system;
- Input a significance level alpha to perform a statistical normality test;
- A Shapiro-Wilk normality test is performed using the values in the first (or only) column of the input file. The p-value obtained by the statistical test is returned. Considering the null hypothesis that the data is normal, and using the significance level alpha given by the user:
- If the returned p-value is less than alpha, the null hypothesis is rejected and the input data is considered not normally distributed;
- Otherwise, the null hypothesis is accepted and the input data is considered normally distributed;
- Using the returned p-value, the user can judge the null hypothesis using any desired significance level;
- A data histogram is plotted with the data separated in bins. Thus, the user can visually see how normally distributed the data is;
- Lastly, a Q-Q plot is also created to compare the input data distribution with the theoretical data distribution of a normal distribution. The closer the points are to an identity line (y = x), the more normally distributed the input data is.
Shiny is a framework that allows users to develop web apps using R and embedded web languages, such as CSS and HTML. Shiny apps focus on objectiveness and simplicity: only one or two R scripts have all the code for the app.
This app development started with knowledge and tools discussed during the course "Data Science Bootcamp" by Fernando Amaral. The app has been upgraded and personalized, adding new functionalities.