Module 4 - Session 4.5a Sampling

efsa LEARNING PROGRAMME

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 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


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


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


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


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


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


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


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


Precision and Accuracy

Not preciseNot accurate

Not preciseAccurate

PreciseNot accurate

AccuratePrecise


Pop Quiz

Representative or bias sample?


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.


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


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…

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


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



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


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


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


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.


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.


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.


Examples of non-probability sampling

You go to a village and speak to the key informants about food security and availability


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


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.


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


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


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

Module 4 - Session 4.5a Sampling

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Transcript of Module 4 - Session 4.5a Sampling