introduction to sampling : censuses vs. sample surveys
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Introduction to Sampling : Censuses vs. Sample Surveys. Module 3 Session 4. 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 - PowerPoint PPT PresentationTRANSCRIPT
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Introduction to Sampling: Censuses vs.
Sample Surveys
Module 3Session 4
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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
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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
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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
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Sampling Frames Sources
Administrative records-eg Hospital records Birth and Death Registers LC lists Voters’ register School registers etc
Construct your own
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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
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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
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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
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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
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Challenges of Conducting Censuses and Large Scale Sample Surveys Challenges of Surveys and Censuses Mubiru
James.ppt
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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
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Advantages of Random Samples Objective and hence inferences based on
them are reliable
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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.
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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
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Disadvantages of Non Random Samples Subjective and hence inferences based on
them are biased Sampling errors can not be estimated
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Types of Errors There are two types of errors, namely:
Sampling errors Non sampling errors
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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
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Sampling in the Research Process Problem Objectives Hypotheses Methodology
Data Sources Target population
Census or sample? If sample?
What is the sampling design?