Introduction to Survey Sampling (Stat 476)
Spring 2020

## General Information

Lecturer Zhiqiang Tan
Office: 459 Hill Center
Email: ztan at stat.rutgers.edu

Lectures: MTh 1:00-1:20pm, PH 111
Office hour: MTh 1:30-2:30pm.
Teaching assistant Xinwei Zhang
Email: xinwei.zhang at rutgers.edu
Office hours: Fri, 2:00-4:00pm, Hill Center 260
Prerequisite Stat 381 (Theory of probability) or equivalent.
Textbook Scheaffer, Mendenhall, Ott, Gerow (2011) Elementary Survey Sampling (7th edition), Duxbury.
Topics
 Introduction & basic concepts Chapter 1, 2, 3 Simple random sampling Chapter 4 Stratified random sampling Chapter 5 Ratio and regression estimation Chapter 6 Systematic sampling Chapter 7 Cluster sampling Chapter 8, 9 Estimating the population size Chapter 10
Exams and Homework There will be 2 midterm exam and a final exam. One page of information sheet, possibly double-sided, is allowed.
Homework will be assigned and collected.
Grading The final grade will be based on the following components with the weights:
 Homework: 20% Midterm Exam #1: 20% Midterm Exam #2: 20% Final Exam: 40%
Makeup policy Make-up exams will only be given if written documentation of a major outside circumstance is provided by a college dean or a doctor.
Students who miss exams without presenting proper documentation in a timely manner will receive a grade of zero.
Homework Assignments HW 1, HW 2, HW 3, HW 4, HW 5, HW 6, HW 7.

Click here for the dataset TEMPS and and here for the dataset SCHOOLS for HW 4.
Click here for the data in Exercise 8.2, here for the data in Exercise 8.8, and here for the data in Exercise 8.20 for HW 5.
Click here for the R codes (as well as data) for simple random sampling for Sampling from Real Populations 8.4 in HW 5.

Solution to textbook problems in HW 1.
Solution to Probability Problems in HW 1.

Solution to textbook problems in HW 2.
Solution to sampling and additional problems in HW 2. See HW2_R.txt for R codes and HW2_R_Output.pdf for R output.

Solution to textbook problems in HW 3.
Solution to additional problems in HW 3. See HW3_R.txt for R codes and HW3_R_Output.pdf for R output.

Solution to textbook and additional problems in HW 4.
Solution to sampling and additional problems in HW 4: HW4_R.txt for R codes and HW4_R_Output.pdf for R output.

Solution to textbook problems in HW 5.
Solution to sampling and additional problems in HW 5: HW5_R.txt for R codes and HW5_R_Output.pdf for R output.

Solution to textbook problems in HW 6.
Solution to sampling and additional problems in HW 6: HW6_R.txt for R codes and HW6_R_Output.pdf for R output.

Solution to textbook problems in HW 7.
Solution to sampling and additional problems in HW 7: HW7_R.txt for R codes and HW7_R_Output.pdf for R output.

Announcements Jan 30
Click here for the plots of binomial and hypergeometric probabilities and here for the R codes.
Feb 6
Feb 13
HW 2 is extended to Thu, Feb 20.
Feb 20
The first midterm will be held on Mon, March 9.
Feb 27
HW 3 is extended to Mon, March 9. The first midterm is re-scheduled to Thu, March 12.
March 2
Click here for the R codes for reading in a data file and handling post-stratification in HW 3.
March 5
March 9
Click here for solutions to the practice exam for the first midterm.
March 17
The first midterm will be held remotely on Monday, March 23, 12:00-3:00PM Eastern time. See more instruction in the email sent to your addresses used on the roster.
March 30
I will use Canvas Annoucements in conjunction with the course website and emails.
Click here for the R codes for ratio estimation with stratified random sampling. Please run the codes yourself and check with the answers obtained by hand in class.
April 2
Click here for the R codes for ratio, regression, and different estimation with simple random sampling. The "tree" dataset used is here.
April 7
Click here for the R codes for cluster sampling. The dataset used is here.
April 9