Week4Assignment - mtcars Predictor Analysis

• write a Shiny App inc. supporting documentation on screen
• deploy this on Rstudio's shiny server and share the Server and UI code on GitHub (See https://github.com/ChrisWoodsSays/9-Dev-Data-Products/tree/master/Week4Assignment/Week4Assignment)
• provide a Reproducible Pitch Presentation

The application must include:

• an input widget which is operated on by server.R code
• reactive output displayed as a result of server calculations
• documentation so a novice user could use the application

The code below is run within the Presentation.

column <- names(mtcars)
description <- c("Miles/(US) gallon","Number of cylinders","Displacement (cu.in.)",
                  "Gross horsepower","Rear axle ratio","Weight (1000 lbs)","1/4 mile time",
                  "Engine (0 = V-shaped, 1 = straight)","Transmission (0 = automatic, 1 = manual)",
                  "Number of forward gears","Number of carburetors")
table<-cbind(column,description)

The code below is then run on the following page.

kable(table)

The analysis is based on the mtcars dataset which has 11 columns/ variables as set out below. Any one of these can be selected as the outcome and then the Server code calculates the p-value for all the other variables as predictors. The lower the p-value, the greater the predictive nature of the variable.

A selectsize input widget is used to choose the Outcome and the values for this are calculated within the Server code.