Mathematical Modeling (MATH 420/620)

Spring 2018 course website

Lectures: 12:00pm-12:50pm, MWF, in PE 104 (map)    
Scheduled Final: 12:10-2:10pm on Friday, 11 May 2018. (PDF of Spring 2018 Finals Schedule; UNR Academic Calendar).
Syllabus: Click here to download (PDF).

Office Hours: MW 1-2pm, Th 12:30-1:30pm, or by appointment, in 220 DMSC.

Textbooks: Introduction to Probability Models (10th) by Sheldon Ross, and Nonlinear Dynamics and Chaos (2nd) by Steve Strogatz.
WebCampus will be used for this course: https://wcl.unr.edu

Software Resources

See my instructions for installing R and LaTeX software.

LaTeX: Use TeXStudio if you don't have a preferred editor. Want to use the cloud instead? Use www.overleaf.com. R: Install R, then RStudio. Also, see my R page and www.statmethods.net to get started using R. Homework Templates: Want to turn in homework that looks like this PDF? Download this zip file and open the TeX document in TeXStudio, or the *.Rnw file in RStudio.

Maxima:A free alternative to Maple for symbolic computations. Download Maxima or the slightly more user friendly version (preferred) wxMaxima. Resources to get started with Maxima: Instant Maxima (PDF) by Steve Ellner. Also, see Richard H. Rand's Introduction to Maxima, or see the Maxima website.

(You may also want to get familiar with software like Matlab, Mathematica, SAS, ArcGIS, etc. available through UNR Remote Services).

Tentative Schedule

Week Monday Wednesday Friday Homework & Notes
1: 1/22-1/26 Syllabus;
Introduction & overview
Software Introduction
r_intro.r
Software continued;
The Modeling Process
Homework 1 (due Weds, 31 Jan): hw1.pdf [hw1.tex]
Solution: hw1-soln.pdf [hw1-soln.Rnw]
2: 1/29-2/2 The Modeling Process (cont'd); Probability Basics
Room: PE 104
Probability Basics
Room: DMSC 106
Probability Basics
Room: PE 104
probability-review.pdf,
probability-distributions.pdf
3: 2/5-2/9 Probability & R
Room: DMSC 106
Probability & R
Room: DMSC 106
Statistics Intro
Room: PE 104
Reading: Ross, Ch.1-2
Homework 2 (due Weds, 14 Feb): hw2.pdf [hw2.tex]
Solutions: hw2-soln.pdf [hw2-soln.Rnw]
4: 2/12-2/16 Estimator Properties
Room: DMSC 106
Maximum Likelihood Estimation
rssmle.R
Room: DMSC 106
Regression
5: 2/19-2/23 Presidents' Day
NO CLASS
MLE Continued
Room: DMSC 106
GLM Intro; Slides: [PDF],[Rmd], iris-logistic.R
Room: PE 104
6: 2/26-3/2 Poisson Processes & Regression
Room: DMSC 106
Poisson Processes & Regression
count-data.zip
Room: DMSC 106
Poisson Processes & Regression
Room: PE 104
Wrap-up: count-data-obs-glm-final.R
7: 3/5-3/9 Poisson Regression
Room: DMSC 106
Poisson Regression
Room: DMSC 106
Markov Chains
Room: PE 104
Homework 3 (due Fri, 16 Mar): hw3.pdf [All files: hw3.zip]
hw3-soln.pdf
8: 3/12-3/16 Markov Chains
Room: DMSC 106
Room: PE 104 Markov chain notes: MCnotes.pdf
9: 3/19-3/23 SPRING BREAK SPRING BREAK SPRING BREAK
10: 3/26-3/30 Room: PE 104
11: 4/2-4/6 Room: PE 104
12: 4/9-4/13 Numerical Solutions to ODEs
euler.R
Exam Review Room: PE 104
13: 4/16-4/20 Exam Example Bifurcation: RM.R
Room: PE 104 Project Information:
project-proposal.pdf (Due 23 April), project-report.pdf
14: 4/23-4/27 Room: PE 104
15: 4/30-5/4 Room: PE 104 Hw4: PDF, TeX (hw4.2.R)
16: 5/7-5/11 Prep Day Scheduled Final 12:10-2:10pm in PE 104