Mathematics 549 - Fall 2008

David Patterson
Math 208
Office hours: M 2-3, Tu 1-2, W 4-5 (except on some dates TBA), Th 1-2:30

Readings from textbook:
Week 1: Chapter 1
Week 2: 2.1-2.4, 2.7 (at least to mid p. 24); Math students: 2.6
Week 3: Chap. 3,4,5,6
Week 4: Chap. 7
Week 5: Chap. 8, 11
Week 6:
Week 7: Chap. 11, 12
Week 8: Chap. 13, 14

  • Syllabus
  • R project (see "An Introduction to R" under Documentation-Manuals for an intro)
  • R reference card
  • Brief introduction to R

    Notes

  • Terminology review
  • Course overview
  • Sampling problems
  • Simple Random Sampling (Chap. 2)
  • Sample Size (Chap. 4)
  • Unequal Probability Sampling (Chap. 6)
  • The Horvitz-Thompson Estimator
  • PPS Sampling - Supplement
  • Ratio Estimation
  • Delta Method
  • Bootstrapping
  • Regression Estimation
  • Ratio/Regression Estimation Supplement
  • Stratified Sampling <
  • Cluster and Systematic Sampling
  • Cluster and Systematic Sampling (Revised)
  • Multistage Sampling
  • Double Sampling
  • Line-Intercept Sampling
  • Some Extensions of Line-Intercept Sampling
  • Detectability and Sampling
  • Distance Sampling (Chap. 17)
  • Distance Sampling, Part 2
  • Adaptive Cluster Sampling

    Homework

  • Homework 1: due Fri., Sept. 12.
  • Homework 2: due Mon., Sept. 29 (note change) Data set: Statepps.dat
  • Homework 3: due Mon., Oct. 13. Data sets: harvest.csv, otters.csv
  • Homework 4: due Mon., Nov. 3. Data sets: fraser.txt, coots.txt, Systematic fucntion
  • Homework 5: due Fri., Nov. 21. Leaf.R, probin.R, ht.R

    Solutions

    Login name and password required.
  • Homework 1 Solutions
  • Homework 2 Solutions
  • Homework 3 Solutions
  • Test 1 Solutions
  • Homework 4 Solutions
  • Homework 5 Solutions

    R scripts

  • Sample size (on p. 18 of notes)
  • PPS Example (from Reading Data in R)
  • Horvitz-Thompson Farm Example (on p. 29 of notes)
  • Ratio Estimation Example (on p. 31 of notes)
  • Bootstrap Example 1 (pp. 45-7 of notes)
  • Bootstrap Example 2 (pp. 48-9 of notes)
  • Regression Estimation Example (pp. 54-55 of notes)
  • Ratio estimation function (p. 56 of notes)
  • Regression estimation function (p. 57 of notes)
  • Stratified random sampling calculations for TV example (p. 66 of notes)
  • Stratified sample size calculations for TV example (pp. 71-2 of notes)
  • Two stage calculations for highway example, part 1 (pp. 92-5 of notes)
  • Two stage calculations for highway example, part 2 (pp. 96-7 of notes)
  • Two stage allocation calculation for highway example (p. 102 of notes)
  • Double sampling calculations for biomass example (pp. 105-6 of notes)
  • Line-intercept calculations for farm example (pp. 117-120 of notes)
  • Line-intercept calculations for farm example using functions probin and ht
  • Function probin To compute probabilities of inclusion (both individual and joint) for line-intercept sampling
  • Function ht To compute Horvitz-Thompson estimate and SE

    Other links

  • USDA publication: Statistical techniques for sampling and monitoring natural resources

    Last updated: 5 December 2008