To use the app, first you can copy the script from the 'Link to App' tab. Open a new shiny web app on RStudio and replace the default content with our app script. Once you've done that, save the document and place it into a folder. Additionally, save the .csv file at the bottom of our script into the same folder that the newly created R file went into. Once you've added the data and app to the same folder, run the app and explore our options. Below is a screenshot of the window that should appear when the app is run. [[A common error that may occur is when the data is not saved in the same folder as the app. Be sure that they are saved together!]] 

The left-side panel contains the user options to change the inputs to make the graphs react. The first optional input that you, the user, can change is called a "slider bar" widget. It is very easy to use. Simply drag the cursor to any point along the bar to change the sample size and view how the graphs react. 

The next two options are connected. These selection options are called "radio buttons". They allow for a single selection of a choice of options. These radio buttons allow you to choose the explanatory and response variables that are graphed on the scatterplot in the server pane on the right side. Note that the default options of House Number are selected and that the graph is a perfect line. This is expected since the house numbers will match up whether graphed on the x or y axis.

Note how the graph changes when different variables are selected. The closer the data lies to the regression line, the stronger correlation exists. For example, weight and BMI are fairly closely related physical measurements and thus have a strong correlation.

The last option that we have created for the app is a "text input" widget. This simply takes the text input and apply it to the title of the graph. Go ahead and give your graph a name!

Now you have an understanding of how our app works! Tinker with the options to explore some of the different measurements that were gathered from the Islands dataset!