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 Statistical Methods for Sample Surveys  posted by  member150_php   on 3/9/2009 Add To Favorites
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Abstract/Syllabus:

## Statistical Methods for Sample Surveys

### Spring 2009

Photo by Argos Panoptes via flickr.com. Creative Commons BY-NC-ND.

Course

Saifuddin Ahmed

#### Offered By

Department of Biostatistics

#### Description

Presents construction of sampling frames, area sampling, methods of estimation, stratified sampling, subsampling, and sampling methods for surveys of human populations. Students use STATA or another comparable package to implement designs and analyses of survey data.

## Syllabus

#### Course Description

Presents construction of sampling frames, area sampling, methods of estimation, stratified sampling, subsampling, and sampling methods for surveys of human populations. Students use STATA or another comparable package to implement designs and analyses of survey data.

#### Course Objectives

Upon successfully completing this course, students will be able to: 1) design and implement surveys with the following sampling designs: simple random, systematic, stratified, cluster and multistage; 2) estimate sample size for different sampling designs in order to estimate population level point estimates and testing null hypothesis; 3) explain and apply intraclass correlation and design-effects (DEFF) for complex surveys; 4) estimate design weights and adjust for non-response.

#### Prerequisites

Statistical Methods in Public Health II or Methods in Biostatistics II

United Nations Department of Economic and Social Affairs: Designing Household Survey Samples. United Nations, 2005.

Levy PS, Lemeshow S: Sampling of Populations: Methods and Applications, 3rd edition. New York: Wiley Interscience, 1999. - Optional

Lohr SL: Sampling: Design and Analysis. Duxbury Press, 2009. - Optional

#### Course Requirements

Laboratory Exercises - 60%

Final Project - 40%

## Schedule

SESSION # TOPIC ACTIVITIES
1 Introduction to sampling Lecture 1
2 Simple Random and Systematic Sampling

Lecture 2

Lab

3 Sample Size and Power Estimation

Lecture 3

Lab

4 Stratified sampling

Lecture 4

Lab

5 Cluster sampling

Lecture 5

Lab

6 Weighting

Lecture 6

Lab

7 Survey errors

Lecture 7

Project/Lab

8 Case Studies Project Review

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