Statistics  5201 Home Page

Statistics 5201

Sampling Methodology in  Finite Populations

Spring 2012

Instructor: Glen  Meeden

office: 313 Ford Hall

office hours: 2:30 - 3:30 TThF or by  appointment

phone: 612-625-8321

e-mail: glen@stat.umn.edu

Teaching Assistant: Brandon Whited

office hours: M 3:00-4:00 and Th  1:00-2:00 in 350 Ford Hall

e-mail: white942@umn.edu

Lecture: 1:25-2:15 MWF

Classroom: 319 Akerman Hall

Text: Sampling: Design and Analysis, 2nd  Edition, by Sharon Lohr and published by Duxbury Press in 2010. (You may use  the 1st edition.)

Here  is a link to Rweb

The inclass midterm exam will be given  on sometime after the spring break. The exam will cover the material in the  first five homework assignments. It will be closed book but you may bring one  8 by 11 formula sheet with whatever information you want on it. You may use  both sides of the sheet. You may not use a calculator. It is enough to  express any numerical answer as a formula which can easily be evaluated using  a calculator.

The final exam will be a take home exam  and it will be handed out on the last day of class.

Syllabus

Announcements

Additional information about  R and Rweb can be found at More on Rweb

To import the Lohr data into a table in  R, use the following commands at the R prompt (>) substituting in the  username and password you were given in class:

library("RCurl")

x<-getURL("http://users.stat.umn.edu/~gmeeden/classes/5201/lohrdata/agsrs.txt",  userpw = "username:password")

myData<-read.table(textConnection(x),  header=T)

Home work assignments

An  optional R homework assignment

Assignment  1

Assignment  2

Assignment  3

Assignment  4

Assignment  5

Assignment  6

Some course handouts

Notes  for the first lecture and the review of probability theory

Some  notation

An  introduction to R given in class

Using  R to draw samples and the Central Limit Theorem

Some  least squares theory

Some  proofs for cluster sampling

Notes  for the calibration lecture

The  model based approach to survey sampling

An  introduction to the Bayesian approach to survey sampling

An  introduction to the survey package in R.

Some  Rweb handouts

Introduction  to Rweb

Table  lookup in Rweb

Simple  random sampling

Estimating  a population mean

Entering  populations into R

Calculating  the ratio estimator for a population total

Calculating  the regression estimator for a population total

Working  with stratified random samples

Working  with cluster samples

Studying  the Horvitz-Thompson Estimator

Variance  estimation of a systematic sample

Variance  estimation for the ratio estimator

Adjusting  the Horvitz-Thompson Estimator

Homework Solutions

Solutions to old exams

In  class Spring 08 midterm

Spring 08 Takehome finalwith  answers to problems 2 and 3 in More answers

Spring  09 Takehome final

In  class Spring 10 midterm

Spring  10 Takehome final

In  class Spring 11 midterm

Spring  11 Takehome final

Spring  12 In class midterm

Spring  12 Takehome final

Spring  13 In class midterm

Spring  13 Takehome final