Lecture schedule -- Spring 2020

10, 15, 17- Jan:1- Introduction to computing using R (HM)

22 & 24 Jan: 2-Using R to manage data (CM)

29 & 31 Jan: 3-Standard statistical tests in R (HM)

5 & 7 Feb: 4- Advanced R programming (CM)

12 & 14 Feb: 5- Applying programming to natural resource management (1) CM

19 & 21 Feb: 6-Applying programming to natural

resource management (2) CM

26 & 28 Feb: 7-Fitting models to data using R– general approaches HM

5 & 7 March: 8-Advanced methods for

model fitting to natural resource

management MC/ CM

11 - 15 March Spring Break

19 & 21 Mar:

9-Using models to guide natural resource decision

making MC/ CM

26 Mar:

10- Applications of decision making models (1) LP cont'd

28 Mar & 2 Apr: 11- Using R for GIS, spatial interpolation. CM

4 & 9 April 12- Applications of decision making models (2) MC

• Incorporating time (dynamics) into decision making
• Decision making under uncertainty

11 April : 13- Big data analysis and applications CM

16 April- 14-Creating applications with RShiny CM

• Shiny app simulating parakeet control

18 April- Discussion/ problem solving

23 April-Graduate student presentations

• Forestland ownership. Garzon, Lee
• Structure from motion accuracy - Wei
• FIA data in Shiny - Porter, Raut

25 April-Graduate student presentations

• Nesting data for northern bobwhite - Justin Hill
• GPS watch accuracy in 3 forest types-Gutierrez-Garzon, Lee
• Yield variability predicted by precip. - Steele

30 April: Last class day