See below for:

Sample Problems for Fall 2007 Exam
NOTE: for the final exam you may use a calculator and AT MOST 2
notebook sheets (single sided) of formulas for reference.

Take-Home Makeup/Extra-Credit for In-Class Test

Getting Started in R
Course topics
Requirements, Grading & Policies
Course handouts
Homework Assignments
Other links

Instructor: Eric V. Slud, Statistics Program

Office hours:  M 1 & 4, Th 11-12, F 1, Room MTH 2314
Telephone:  (301) 405-5469
E-mail: evs@math.umd.edu (the best way to reach me)

Textbook:  Lohr, S. L. (1999).  Sampling: Design and Analysis.  
       Pacific Grove, CA: Duxbury.    ISBN 0-534-35361-4

Prerequisite:  A semester of statistics at the level of STAT 401 or 420.

Course Description:

Sampling refers to the statistical techniques used in political polls,
marketing surveys, federal data gathering and many areas of social
science and public health.

This course provides an introduction to methods of sampling and
analyzing data from finite populations from both a theoretical and
applied perspective. It is intended for Statistics and Mathematics
students interested in applications and for students in the Applied
Statistics track of the Survey Methodology program, as well as
students in disciplines such as business, life science or social
science who need sampling in their research.

 
The mathematics used in the course is not deep, but it can be
intricate. It is essential that you understand basic statistical
concepts such as point estimation, confidence limits, and the
central limit theorem.

STAT 440 is part of the required material for the MATH/STAT/AMSC
MA and PhD Written Examinations in Applied Statistics.

Topics:       for departmental syllabus click here

• Basic concepts: sample design, bias, sampling and
       nonsampling errors.
• Simple random sampling: statistics, estimates, confidence
       limits, ratio and regression estimators.
• Stratified sampling.
• Cluster sampling and complex surveys.
• Nonresponse: effects and adjustments.
• Advanced topics: variance estimation, linearization metohds,
       and regression in complex surveys.

Coverage in Lohr's book:

Chapters 1--8 plus topics from Chapters 9 and 11.

References:

Cochran, W. J. (1977).  Sampling Techniques  (3rd. ed.).
     New York: J. Wiley.

Sarndal, C.-E., Swensson, B., and Wretman, J. (1992).  Model
     Assisted Survey Sampling.  New York: Springer.

Course Requirements and Grading:

There will be an in-class midterm on Monday, Oct. 29, and a final
exam on Monday, Dec. 17 from 4--6 p.m. There will be frequent
homework assignments, 7 in all, including both theoretical
and applied problems. Grades will be based on the midterm (25%),
homework (40%), and the in-class final exam (35%) .

Course Policies:

(i) As part of the applied homework assignments, students will be
expected to do arithmetic calculations on the computer, which will
sometimes involve a small amount of programming. Students may
choose the language or platform, which may range from Spreadsheets
to SAS to R or Splus. However, all computational illustrations in
the course and all computer help offered in an office-hour setting
will be restricted to Splus and R.

For the systematic Introduction to R and R reference manual
distributed with the R software, either download from the R website
or simply invoke the command

> help.start()

from within R. For slightly less extensive introductory tutorials
in R, click CUNY or Illinois State or Union College.

(ii) No homework will be accepted late.

(iii) All homeworks for students taking the course on campus should
be handed in as hard-copy on or before the due date.

Homework Assignments.

Homework solutions including numerical answers, a little verbal discussion, and
R scripts for the computations, can be found here.

(1) Through September 12, read Chapters 1 and 2 of Lohr text.
First HW Due Mon., Sept. 17. Ch. 2, Problems 1, 3, 6, 8, 12, 18, 25.

(2) Reading for the next 2 weeks, through Wed. Sept 26, is Chapter 3.
Second HW Due Monday Oct. 1. Ch. 2 Problem 13 (p.55), and
Ch. 3, Problems 4, 5, 6, 11, 16.

For an R script relating to (part of) Problem 7 -- similar to the assigned
problems 5 and 6 -- in Chapter 3, click here.

(3) Reading for the next 2 weeks, through Wed. Oct. 10, is Chapter 4.
Third HW Due Monday Oct. 15. Ch.3 # 22 and
Ch. 4 Problems 1(a), (c), (d), 5, 10, 15, 17, 23.

(4) HW4 based on reading in Ch.5, due-date extended to Monday, Oct. 29, 2007:
Ch.5 Problems #4, 9, 12, 15, 17.

The in-class test on Monday, Oct. 29, covered material through Sec. 5.3.
For an Extra Credit Problem Set on which you can earn up to 60% of the points
you missed on the in-class test click here. The due-date for the Take-Home is
Monday, Nov. 19. (Note that the HW5 due date is extended to Wednesday Nov. 21.)
For solutions to the Take-Home, click here.

(5) HW5 reading through Friday, November 16: finish Ch.5
omitting only Sec. 5.7; also read Ch.6.1-6.6.
Problem Set 5, due Wednesday Nov. 21: Ch.5, #22; Ch. 6, #4 (show your
computer code or say exactly what you did!), and #5, 9, 13, 15, 20, 21.

(6) HW6 reading through Friday December 7: Ch.7 Sec. 7.6, Chapter 8,
and Chapter 9 sections 9.1, 9.2, 9.3.2.
Problem Set 6, due Monday December 10: Ch. 7, #9, 16; Ch. 8, #8; Ch. 9, #4, 9, 11.