Tree volume is a key measurement for businesses involved in the harvesting of trees for lumber.

It is understood to be related to two parameters:

• Diameter of a tree 4-1/2 feet above the ground (Girth in R data)

• Merchantable height - the length of the trunk that is usable

The focus of this project is to use a shiny app employing regression analysis to predict volume from user supplied Height and Diameter (called Girth).

• Regression data is pulled from the 'trees' dataset in the R base package.

• Acknowledgement: The plots and final model are developed at https://www.dataquest.io/blog/statistical-learning-for-predictive-modeling-r

The final prediction equation is:

• Volume = 69.40 - 5.86(Girth) - 1.30(Height) + 0.13(Girth * Height)
• R-squared for the model is 0.97

To use the prediction model presented on the previous slide, the user should do the following:

• Activate the Shiny App
• Choose a tree diameter (or Girth)
• Choose a height of the trunk
• Click on the Submit button

A scatter plot showing the Height/Girth combinations for the sample data is displayed.

The predicted volume will appear in the Main window beneath this plot.