module 4 - session 4.5a sampling
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Module 4 - Session 4.5a Sampling. Learning Objectives. By the end of this session, you should be able to: Describe the different types of sampling methods and their strengths and weaknesses Select an appropriate sampling method - PowerPoint PPT PresentationTRANSCRIPT
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Module 4 - Session 4.5a
Sampling
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Learning Objectives
By the end of this session, you should be able to:
Describe the different types of sampling methods and their strengths and weaknesses
Select an appropriate sampling method Be aware of how sampling methods can be linked to
the collection, analysis, and interpretation of data Know the sample designs that can be used for an
EFSA and Rapid Rural Assessment
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Sampling Overview
Sampling is the process of selecting a small number of people from a larger group of people
The goal of sampling is to estimate something in a larger group
To estimate something in a larger group, the smaller group must be representative of the larger group
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Sampling Overview
Sampling can be a complicated process and can be simplified by understanding a few key elements
Non-proportional sampling
Accuracy
Random selection
Precision
Representative
Bias
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Sampling Overview Sampling can be a complicated process and can be
simplified by understanding a few key elements
Sampling is done because it is cheaper and quicker than questioning everyone in the area and will give you accurate information if done right
there are 600,000 women in the provinceten teams can interview 60 women a day interviewing 200 women will take 3.3 days interviewing 600,000 women will take 2.7 years
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Sampling Overview Sampling can be a complicated process and can be
simplified by understanding a few key elements
Sampling is done because it is cheaper and quicker than questioning everyone in the area
The challenge in sampling is to select the right group of people to interview accurately interpret the information collected
from the smaller sampled group to the larger target population
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First, the people…Target Population
The people that you want to provide assistance
Sample Sample PopulationPopulation
The group of people that you The group of people that you want to interviewwant to interview
Respondent The people that you interview
Analysis unit Who the survey data refer to
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then a few key elements…Random: Everyone has an equal
chance of being interviewed
Bias:Bias: Some people have greater Some people have greater chance of being chance of being interviewed than othersinterviewed than others
Representative: The information from the sample is similar to the information if everybody in the target population was interviewed
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then the numbers…
Precision Ability to get the same results Ability to get the same results if you do the survey again if you do the survey again using same questionnaire and using same questionnaire and sampling designsampling design
AccuracyAccuracy Ability to get results close to Ability to get results close to the truththe truth
Validity Ability to measure what you want to measure
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Precision and Accuracy
Not preciseNot accurate
Not preciseAccurate
PreciseNot accurate
AccuratePrecise
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Pop Quiz
Representative or bias sample?
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Representative or biased sample?
A survey of malnutrition in children uses radio announcements to ask women to bring their child to the health clinic on Tuesday morning.
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biased…
Mothers who use the clinic may not be representative of all mothers in the population
Only people with a radio can hear about the survey
Mothers must go to the clinic on Tuesday
Mothers who use the clinic may not be representative of all mothers in the population
Only people with a radio can hear about the survey
Mothers must go to the clinic on Tuesday
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All the houses in a village is numbered. All the houses in a village is numbered. You randomly select 1% of the houses and You randomly select 1% of the houses and write down the house number that has write down the house number that has been selected. You go to the house been selected. You go to the house number and interview the occupants.number and interview the occupants.
Representative or biased sample?
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representative…
You had a list of all the houses in the village
Every house had an equal chance of being selected
You were able to go the houses that were selected
This is an example of simple random selection
You had a list of all the houses in the village
Every house had an equal chance of being selected
You were able to go the houses that were selected
This is an example of simple random selection
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An NGO website asks online visitors to An NGO website asks online visitors to answer questions on whether NGOs answer questions on whether NGOs appropriately use food assistance in appropriately use food assistance in emergenciesemergencies
Representative or biased sample?
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biased…
People who visit the NGO home page may not be representative of the humanitarian community
People with strong opinions about the subject are more likely to participate
This is an example of self-selection bias where participants choose to be sampled
People who visit the NGO home page may not be representative of the humanitarian community
People with strong opinions about the subject are more likely to participate
This is an example of self-selection bias where participants choose to be sampled
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Errors in Sampling
Sampling
Not representative of target population
Random selection of respondents
Too few participants
Recruit more participants
Measurement
Confusing questionsPilot questions
Interviewer suggests responsesTrain interviewers
Response
People refuse to be interviewedTrain interviewers
People give response they think you wantTrain interviewers
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and the two approaches…
Probability Random methods decide who is selected and the chance of a person being selected is known
Non-probability
Subjective judgment is used to select the sample and you do not know the chance of a person being selected
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Examples of probability sampling
You have a list of 35,000 people registered in a refugee camp. You sample every 350th person on the list. The chance of being selected is 350/35,000 or 1 in 1000.
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Examples of probability sampling
You have the names of the 45 villages in a province and write the names of each village on a piece of paper. You put all the pieces of paper in a glass jar, mix the pieces of paper and pick out 5 pieces. The chance of a village being selected is 5 out of 45 or 1 in 9.
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Examples of non-probability sampling
You go to the village square and ask people in the market about the kind of food they have at their house.
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Examples of non-probability sampling
You go to a village and speak to the key informants about food security and availability
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When to Use Probability and
Non-probability Sampling Probability sampling
Number or percent of people with a characteristic Assess small changes when monitoring or evaluating a
program Nutritional or health surveys use probability sampling
Non-probability sampling Some information is more important than an accurate and
precise number Pilot testing Rapid appraisal methods often use non-probability sampling
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The big difference…
Probability sampling – a lot of effort is taken to select the person to interview because that person represents many other people. That process must be replicated for each person that is interviewed.
Non-probability sampling – there is less restrictions on selecting the person to interview.
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so…why bother with probability sampling?
Sample is representative of a larger population
Results can be generalized
Minimizes bias for selecting people to be interviewed
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so…why bother withnon-probability sampling?
Easy and fast recruitment
Explore a problem and some basic idea of a solution
Provide insight and comprehension of a situation
Good at probing below the surface for affective drives and subconscious motivations
May be only realistic option in an emergency
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Summary
Sampling gathers data on a small group of people to help understand what is going on in a larger group
Probability and non-probability sampling are the two major sampling designs
The challenge in sampling is to 1) select the right group of people to interview and 2) accurately interpret the information collected from the smaller sampled group to the larger target population