Lecture 2 (Tues., Aug. 21): Ch. 2. Notation. Simple random samples. Population quantities and sample estimates from simple random samples.
HW Assignment 1: Problems 1.4, 1.13, 2.1, 2.7, 2.11, 2.17 (use only 18 hole courses, golfsrs.dat, sas input code), 2.22. Due Thurs., Aug. 30.
Lecture 3 (Thurs., Aug. 23): Confidence intervals, proportions, and sample size calculations.
Lecture 4 (Tues., Aug. 28): Derivation of the variance of the sample mean from an SRS. Review all of Ch. 2.
Lecture 5 (Thurs., Aug. 30): Begin stratified sampling, Ch. 3: basics, proportion estimation, and proc surveymeans.
HW Assignment 2: Problems 2.28, E1 (sent by e-mail), 3.6, 3.20 (radon.dat, data set description,sas input code), 3.23, 3.25. Due Thursday, Sept. 13.
Lecture 6 (Tues., Sept. 4): Stratified sampling: proportional allocation, optimal allocation.
Lecture 7 (Thurs., Sept. 6): Median estimation, choosing strata.
Lecture 8 (Tues., Sept. 11): Begin Ch. 4, ratio estimators, delta method variance estimation.
Lecture 9 (Thurs., Sept. 13): Domain estimation from SRS using ratio est., regression estimators.
HW Assignment 3: 4.1, 4.3 (data), 4.15, 4.16, 4.28, 4.32, 4.38 (instructions). Due Thurs., Sept. 27.
Lecture 10 (Tues., Sept. 18): Regression and diffference estimators
Lecture 11 (Thurs., Sept. 20): Difference estimators.
Lecture 12 (Tues., Sept. 25):Poststratification, combined and separate estimators in stratified case.
Lecture 13 (Thurs., Sept. 27): Begin Ch. 5, cluster sampling.
Mid-Term Exam (Tues., Oct. 2, 8:00 - 10:00 a.m.): Covers Chapters 1-4. You may use one side of an 8.5 by 11 sheet of paper with hand-written notes during the exam. Calculators will be needed.
Lecture 14 (Tues., Oct. 9): Cluster sampling - Unequal size clusters.
Lecture 15 (Thurs., Oct. 11): Two-stage cluster sampling.
HW Assignment 4: 5.2, 5.4 (journal.txt), 5.6, 5.11, 5.21 (ozone.dat, sas input code), 5.22. Due Thurs., Oct. 26.
Lecture 16 (Tues., Oct. 16): Choice of m and n in two-stage cluster sampling. Systematic sampling.
Lecture 17 (Thurs., Oct. 18): Systematic sampling continued.
Lecture 18 (Tues., Oct. 23): Smith's b, optimal cluster size for single stage cluster sampling, and traffic cases example.
Lecture 19 (Thurs., Oct. 25): Ch. 6: Sampling with unequal probabilities with replacement.
HW Assignment 5: E2 (plot), 6.2a, 6.8, 6.13 (statepop.dat, see Example 6.5), 6.18, 6.20. Due Thursday, Nov. 8.
Lecture 20 (Tues., Oct. 29): Ch. 6: Sampling with unequal probabilities with replacement continued.
Lecture 21 (Thurs., Nov. 1): Ch. 6: Sampling with unequal probabilities without replacement, the Horvitz-Thompson estimator.
Lecture 22 (Tues., Nov. 6): Ch. 6 review and Ex. 6.11.
Lecture 23 (Thurs., Nov. 8): Begin Area Frame Sampling.
Lecture 24 (Tues., Nov. 13): Special session on Nate Silver's 538 method and the quality of the polls in the 2012 election.
Lecture 25 (Thurs., Nov. 5): Continue Area Frame Sampling.
Lecture 26 (Tues., Nov. 20): Ch. 7, complex designs. Gambia example. Ch. 8 Double sampling for nonresponse.
Lecture 27 (Tues., Nov. 27): Ch. 8: use of callbacks for nonresponse and weighting methods for nonresponse.
Final Exam, Thurs., Dec. 6, 8:00 - 11:00 a.m. Covers Chapters 1-8, but the main emphasis will be on Chapters 5-6 and Area Frame Sampling (not in the text). You may use both sides of an 8.5 by 11 sheet of paper with hand-written notes during the exam. Calculators may be needed.