This project was created for the Developing Data Products course as part of the Data Science Specialization offered through Coursera from Johns Hopkins University.
The source code files for this project can be found on GitHub:
2024-08-21
This project was created for the Developing Data Products course as part of the Data Science Specialization offered through Coursera from Johns Hopkins University.
The source code files for this project can be found on GitHub:
The course project is a two part peer-graded assignment:
Create a Shiny application and deploy it on RStudio’s servers
Use Slidify or RStudio Presenter to prepare a reproducible pitch presentation about your application.
The name of the Shiny application developed for this project is the Motor Trend Data Analysis Application and is hosted on RStudio’s shinyapps.io hosted service:
Motor Trend Data Analysis is an interactive Shiny application that uses linear regression modeling techniques to estimate fuel consumption (MPG) in 32 automobiles (1973-74 models) based on 11 aspects of automobile design and performance.
The mtcars dataset is comprised of data that was was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 11 aspects of automobile design and performance for 32 automobiles (1973-74 models).
The mtcars dataset is a data frame with 32 observations on 11 (numeric) variables.