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Stratified and Cluster Sampling: A Comparative Analysis, Lecture notes of Medical statistics

An in-depth analysis of stratified and cluster sampling techniques, with real-life examples and calculations. The lecture covers the definitions, advantages, and disadvantages of both methods, as well as their applications in estimating population parameters.

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Stratified and Cluster Sampling
Lecture 8
Sections 2.6, 2.8
Robb T. Koether
Hampden-Sydney College
Tue, Jan 26, 2010
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Stratified and Cluster Sampling

Lecture 8 Sections 2.6, 2.

Robb T. Koether

Hampden-Sydney College

Tue, Jan 26, 2010

Outline

(^1) Introduction

(^2) Stratified Random Samples

(^3) Estimating Parameters

(^4) Cluster Samples

(^5) Stratified vs. Cluster

(^6) Assignment

Introduction

Suppose we want to measure support for the recent Senate health-care bill in Massachusetts.

Introduction

Suppose we want to measure support for the recent Senate health-care bill in Massachusetts. Suppose further that we know that the Massachusetts population is 36% Democrat, 12% Republican, and 52% Independent.

Introduction

Suppose we want to measure support for the recent Senate health-care bill in Massachusetts. Suppose further that we know that the Massachusetts population is 36% Democrat, 12% Republican, and 52% Independent. Suppose even further that we suspect that party affiliation is a relevant variable. We plan to take a sample of 100 individuals.

Introduction

Suppose we want to measure support for the recent Senate health-care bill in Massachusetts. Suppose further that we know that the Massachusetts population is 36% Democrat, 12% Republican, and 52% Independent. Suppose even further that we suspect that party affiliation is a relevant variable. We plan to take a sample of 100 individuals. What might go wrong if we take a simple random sample?

Introduction

We could choose 36 Democrats, 12 Republicans, and 52 Independents.

Introduction

We could choose 36 Democrats, 12 Republicans, and 52 Independents. What if we chose to survey 25 Democrats, 25 Republicans, and 50 Independents?

Outline

(^1) Introduction

(^2) Stratified Random Samples

(^3) Estimating Parameters

(^4) Cluster Samples

(^5) Stratified vs. Cluster

(^6) Assignment

Stratified Random Sample

Definition (Homogeneous)

A group is homogeneous if its member all have similar characteristics with regard to a variable of interest.

Definition (Stratum)

A stratum is a homogeneous subset of the population.

Definition (Stratified random sampling)

Stratified random sampling is a sampling method in which the population is first divided into strata. Then a simple random sample is taken from each stratum. The combined results constitute the sample.

Stratified Random Sampling

R I D

The strata

Stratified Random Sampling

R Y I D

N N

Select 3 Republicans

Stratified Random Sampling

R Y I D

N N Y

N

Y

Y

N

Select 2 Independents

Outline

(^1) Introduction

(^2) Stratified Random Samples

(^3) Estimating Parameters

(^4) Cluster Samples

(^5) Stratified vs. Cluster

(^6) Assignment