Coursera: Developing Data Products :Shiny Application and R Presentation

This presentation is second half of the assignemnt of week 4, Developing Data Products course from Coursera (https://www.coursera.org/learn/data-products).

The presentation was generated using RStudio(https://www.rstudio.com) and Slidify(http://slidify.org) framework.

The dataset used in the application is Motor Trend Car Road Tests(mtcars), which was taken from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles.

str(mtcars)

'data.frame':   32 obs. of  11 variables:
 $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

Application:

In the prediction model ,created three models for the prediction of horsepower of the car . Model 1 indicates the linear model with miles per gallon and in the second model we have increased the predecessor (mpg+wt) and checked the model ,model 3 (mpg+wt+disp) predicated the horsepower. calculated and tested the predication.Below link will shows the application. https://nikhilgupta1611.shinyapps.io/application/