This is a deliverable for the course Developing Data Products as part of the Coursera Data Science Specialization.

Instructions:

1. Write a shiny application with associated supporting documentation. The documentation should be thought of as whatever a user will need to get started using your application.
2. Deploy the application on Rstudio’s shiny server
3. Share the application link by pasting it into the provided text box
4. Share your server.R and ui.R code on github

Using the data provided by Galton Families dataset, we fit a linear model to predict a child’s height based on the gender and parent’s average height.

The application is running on:

(https://czuewj-raamses-d0az.shinyapps.io/MyappDDP/)

ui.R, and Server.R Code in my github repository:

(https://github.com/Raamses-DS/Developing-Data-Products-Course/tree/main)

The data used in the construction of this app comes from the GaltonFamilies dataset. Here we can observe the structure of the dataframe used:

## 'data.frame':    934 obs. of  8 variables:
##  $ family         : Factor w/ 205 levels "001","002","003",..: 1 1 1 1 2 2 2 2 3 3 ...
##  $ father         : num  78.5 78.5 78.5 78.5 75.5 75.5 75.5 75.5 75 75 ...
##  $ mother         : num  67 67 67 67 66.5 66.5 66.5 66.5 64 64 ...
##  $ midparentHeight: num  75.4 75.4 75.4 75.4 73.7 ...
##  $ children       : int  4 4 4 4 4 4 4 4 2 2 ...
##  $ childNum       : int  1 2 3 4 1 2 3 4 1 2 ...
##  $ gender         : Factor w/ 2 levels "female","male": 2 1 1 1 2 2 1 1 2 1 ...
##  $ childHeight    : num  73.2 69.2 69 69 73.5 72.5 65.5 65.5 71 68 ...

In the scatterplot below are represented the data used for the prediction model.It is important to note that the unit of cm is used in the app, for which the corresponding unit conversion is carried out.