1

Introduction to Sampling: Censuses vs.

Sample Surveys

Module 3

Session 4

2

Session Objectives

Distinguish between censuses and sample surveys Demonstrate the linkages between censuses and

surveys Discuss the challenges of conducting censuses and

large scale surveys in Uganda Distinguish between random and non random samples Identify the types and/or sources of errors in censuses

and surveys Discuss how errors can be minimised in censuses and

surveys

3

Reminder of Definitions

Population: totality of all units of interest Sample: part/subset of the population Censuses: inquiries that cover the whole population eg.

Uganda Population and Housing Census, CIS, EMIS, HMIS, LOGICS, etc

Sample surveys are inquiries that cover part/subset of the population eg. UDHS, UNHS, NSDS, etc

Sampling Frame: list of distinct and distinguishable units in the population of interest; beginning step in almost all random sampling schemes, e.g. numbers written on households before the census night

4

Other Definitions

Defacto census- covers all persons found within the borders of a particular territory/country at a particular point in time-census night

Dejure census-tallies people according to their regular or legal residence

5

Sampling Frames

Sources Administrative records-eg

Hospital records Birth and Death Registers LC lists Voters’ register School registers etc

Construct your own

6

Disadvantages of various sources of sampling frames

Administrative records may not be up to date

Constructing your own may be too costly especially in large scale surveys

7

Role of censuses in Uganda

Provide benchmark data for monitoring, planning and policy formulation eg we need data for UPE monitoring, poverty monitoring Election monitoring Resource allocation

8

Role of censuses in Uganda (cont.)

Provide small area statistics - basic data disaggregated to the lowest administrative unit e.g we use census data to know the number of people in each village, sub county and district for planning purposes

Show the actual status of the various indicators

Health indicators-mortality, disease prevalence

Fertility trends, population growth rate

9

Linkages between censuses and sample surveys

Sample surveys can be used as a substitute for censuses

Sample surveys can be used to supplement census data

Sample surveys can be used to pretest census materials, procedures and methods

Censuses are used as a basis for surveys conducted between censuses

Sample surveys can be used to monitor census results

10

Challenges of Conducting Censuses and Large Scale Sample Surveys

Challenges of Surveys and Censuses Mubiru James.ppt

11

Types of Samples

There two types of samples: Random and Non random samples

Random samples are those whose composition is not influenced by the sampler

Non Random samples are those whose composition is influenced by the sampler

12

Advantages of Random Samples

Objective and hence inferences based on them are reliable

13

Disadvantages of Random Samples

Costly to select Need skilled manpower to get a random

sample For some surveys, random sampling may not

be the best because the sample may not provide the required data.

14

Advantages of Non Random Samples

Easy and cheap to select since selection and substitution can be done at will

Since they are done at will, the data needed can be easily obtained

15

Disadvantages of Non Random Samples

Subjective and hence inferences based on them are biased

Sampling errors can not be estimated

16

Types of Errors

There are two types of errors, namely: Sampling errors Non sampling errors

17

Sampling Errors/Biases

Sampling errors are absent in censuses Their causes include:

Use of defective sampling frame Use of defective sampling procedures Use of an estimation method that does not

correspond to the sampling design

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Non Sampling Errors

Non sampling errors occur both in censuses and sample surveys but are more pronounced in censuses

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Sources of Non sampling Errors

Defective sampling frames resulting into coverage errors Under coverage Over coverage

Conceptual problems Physical environment Inadequacy of enumerators and supervisors

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Sources continued

Language problems – translation Problems of measurement Response problems Non response problems Poor cartographic work Poorly designed questionnaires/instruments Poorly trained enumerators/supervisors Unqualified enumerators/supervisors

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How Errors can be Minimised

Supervision Training Use of the appropriate estimation method Publicity of the survey Testing the survey instruments

22

Sampling in the Research Process

Problem Objectives Hypotheses Methodology

Data Sources Target population

Census or sample? If sample?

What is the sampling design?