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 Construct your own
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

18. Non Sampling Errors
Non sampling errors occur both in censuses and sample surveys but are more pronounced in censuses

19. 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

20. 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

21. 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?