Developing Data Products Week 4 Course Project

Ashley Thompson
25/11/2021

Introduction

The application, created with Shiny, can be used to predict a value for fertility in Switzerland 1888 (‘common standardized fertility measure’), using a slider that represents the percentage of males involved in agriculture as occupation

Application link

Source code link

Data information

The data is from the swiss dataset. For this application we are only using the Fertility and Agriculture variables.

library(datasets)
library(dplyr)
sws <- select(swiss, 1:2)
head(sws)

             Fertility Agriculture
Courtelary        80.2        17.0
Delemont          83.1        45.1
Franches-Mnt      92.5        39.7
Moutier           85.8        36.5
Neuveville        76.9        43.5
Porrentruy        76.1        35.3

Calculations

A prediction model is made from the swiss data, and then the user selects an Agricultural percentage with a slider, and the resulting predicted Fertility is displayed.

##example using 85 as the input
AgInput <- 85
modelAg <- lm(Fertility ~ Agriculture, data = sws)
modelAgPred <- predict(modelAg, newdata = data.frame(Agriculture = AgInput))

modelAgPred

       1 
76.81152

Example of the plot output

A plot is created showing:

  • The actual data as black points
  • The linear model line as a red line
  • The predicted value as a red dot

plot of chunk unnamed-chunk-3