Post on 15-Jul-2015
Sampling Design, Questionnaire Design & Data
Indraneel BhowmikTripura University
1@ICFAI University, 22nd Jan 2015
Data
Types• Quantitative- numerical• Qualitative- non numerical
Collected by • Individual researchers, • Development planners, • Donor agencies, • Any other institutions
2ICFAI University, 22nd Jan 2015
Data Collection......... is any process of preparing and collecting
data
The purpose of data collection is to-• obtain information • keep on record, • make decisions about important issues,
or• pass information on to others
Data are primarily collected to provide information regarding a
specific topic improve the decision-making by
focusing on objective information
I think the problem is... becomes... The data indicate the problem is
3ICFAI University, 22nd Jan 2015
However
Simply collecting data is not enough- relevant/ specific data is needed to tell what is occurring
The key issue is not:
How do we collect data?
ButBut:
How do we obtain useful data?
Need-
a well-defined Data Collection process
4ICFAI University, 22nd Jan 2015
ISSUES TO CONSIDER
• What is your research question?• What is your target population?• What do you know about this
population? • Do you have a sample frame?• What shape is it in?• Do you have an existing
Questionnaire/ Schedule?• By when do you need your
data?• How much money do you have?
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Determinants of the Mode of Data Collection…..
Population+
Characteristics Of The Sample+
Types of Questions+
Question Topic+
Response Rate+
Cost ₹+
Time
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Sampling Sampling or Census → to be decided by
the researcher Choice → governed by the discipline
Social anthropologists- Social anthropologists- complete enumeration.
Data from each unit of the population- “participant-observation”.
Economists prefer the sampling Advantages Advantages of sampling method
less less workloadworkload better better control over data collection control over data collection
process process reduction reduction of non-sampling errorsof non-sampling errors
Disadvantage of sampling method Sampling errors
However EasierEasier to control sampling errors as
compared to non-sampling errors. Sampling errors are scientificallyscientifically
controllable.
Thus, it is preferablepreferable to work with a sample
rather than going in for complete
enumeration. 7ICFAI University, 22nd Jan 2015
Drawing a Sample1. Define the target population
keeping in view the objectives of the study and then draw a sample
2. The sample could be a ‘probability probability samplesample’ or a ‘non-probabilitynon-probability’ or ‘purposive samplepurposive sample’
3. Probability sample - each member of the population has a known non-zero probability of being selected.– Examples: random sampling,
systematic sampling, stratified random sampling etc.
1. Non-probability or purposive sample - members are selected from the population in some non-random manner– Examples: Convenience sampling,
judgment sampling, quota sampling etc.
8ICFAI University, 22nd Jan 2015
Probability Sample – Types• Random sampling - purest form
– Each member of the population has an equalequal chance
• Systematic sampling -– With the sample size being determined, every every
nnthth record is selected from the population– Simpler than random sampling technique – FrequentlyFrequently used to select a specified number
of records from a computer file• Cluster Random Sampling-
– Divide Population into clusters– Randomly sample Clusters– Measure all units within sampled clusters
• Stratified Random sampling – Most Common– Divide population into non-overlapping
groups (Strata)- N1+N2+ ….+Ni = N; – Yardsticks- landholdings, asset holdings,
incomes, caste, religion, occupation etc.– Draw sample with probabilities proportional
to size of each stratum (PPS sampling)– Reduces sampling error - each stratum is
homogeneous Operational problems
Information necessary for stratification may not be available at the beginning of the work.
9ICFAI University, 22nd Jan 2015
Non- Probability Sample• Convenience (Accidental or Haphazard)
sampling – – Often during preliminarypreliminary research efforts
to get a gross estimate of the results– Selected because they are convenientconvenient
(Man on the street)• Judgment (Purposive) sampling –
– Extension of convenience sampling– Selected on judgment, to serve the
purpose – Ex: draw the entire sample from one
"representative" village, even though the population includes a cluster of villages
• Expert Sampling– Assembling persons with known
experience and expertise (sub-case of purposive)
• Quota sampling – – Non-probability equivalent of stratified
sampling– IdentifiesIdentifies the stratums and their
proportions; then convenience or judgment sampling is used to select the required number from each stratum
• Snowball Sampling- – Identify somebody meeting the criteria,
use him/her for identifying others10ICFAI University, 22nd Jan 2015
Choosing -Random or Purposive• Sociologists and social anthropologists prefer
purposive sampling– May Work for studying a typical social/economic
phenomenon– but it does not help to obtain reliable estimates
• Statisticians prefer random sampling as it is free from any purposiveness or bias.
• Economists choose between purposive & random depending upon the nature of the problem in hand
• Rudra (1989) – – Purposive for studying a social phenomenon more
intensively, subsequently random for testing the hypotheses for generalisation
– method of “randomising the population rather than randomising the sample”
– Ex: to draw a sample of AWs -not necessary to prepare complete village listing, just walk randomly across village & find some labourers working or gossiping
– meeting them there you could fix your sample• Olsen (1993) –
– method of “creative augmentation” when some sensitive information is needed
– find out some households/persons with the characteristic you are looking for
– utilise them as your informants to augment the list 11ICFAI University, 22nd Jan 2015
Sample Size Misconception among some researchers that
larger the sample size, it is better Efficiency of a sample scheme
does not depend on sample size alone depends both on the size of sample (n) and
population variance (σ2). For higher value of σ2 , higher should be n.
• Formula for calculation of variance for distribution of sample mean [V(m)]– V(m) = (σ2)/n
or, n= (σ2)/ V(m)
when , σ2 = 0; n=1 is enough
• To know the population variance (σ2)- – Preliminary work and pilot surveys can help.
Reading past literature and/or discussions with knowledgeable persons - very useful
Israel (1992, 2009, 2013)- provides a table on the desirable sample size with respect to the population http://edis.ifas.ufl.edu/pd006
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BASIC SURVEY DESIGNS
• Cross-Sectional Surveys: Data are collected at one point in time from a sample selected to represent a larger population.
• Longitudinal Surveys = Trend, Cohort, and Panel – Trend: Surveys of sample
population at different points in time
– Cohort: Study of same population each time data are collected, although samples studied may be different
– Panel: Collection of data at various time points with the same sample of respondents.
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Questionnaire and schedule are not the same……………………
• Questionnaire can be sent via mail via mail but schedule is done only personally
• Questionnaire is cheapercheaper method than schedule (for schedule you have to move everywhere)
• Questionnaire can be returned without answering all the questions but, in schedule, enumerator ensures the filling ensures the filling all the questions
• Questionnaire can be filled by anyone but schedule is always filled by enumerator
• Respondent should be literate & co-operative in Questionnaire but schedule can be used for illiterates
• Risk of incomplete & wrong information is more in Questionnaire
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Questionnaire Design
One of the most critical stages of survey research designs
Using common sense and good grammar is a necessary condition but not a satisfactory one…..
It is erroneous to assume that people will understand the questions….
They may• not simply know about the topic, • be unawareunaware of the issue, • lack any interest, • confuseconfuse it with something else, or• simply refuse to answer
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So, how do we go.........1.1. RelevantRelevant- no unnecessary information
2.2. AccuracyAccuracy- information is reliable &valid
3. Avoid Ambiguity, Confusion, & Vagueness- use simple, understandable, unbiased, unambiguous words; e.g- marital status
4.4. No Double Barreled No Double Barreled Query- each question should be about one and only one issue
5. Avoid Avoid LeadingLeading Questions- e.g.,- ‘You, don’t smoke, do you?
6. Avoid Avoid LoadedLoaded Questions- e.g., Spouse beating
7. Do not over Tax over Tax Respondent's Memory
8. Arrange Questions in Proper Sequence- Start with easier things and then build up (funnel technique)
9. Use Use Filter Filter Question, if Needed
10.10. Avoid Avoid OverlappingOverlapping response category16ICFAI University, 22nd Jan 2015
Layout of the questionnaire
• Two Two issues- – Physical layout of the questionnaire and – Format of questions and responses.
• Number each question and put identifying information
• Do not cramp questions or create confusing appearance
• Make a cover sheet cover sheet for admin purposes
• Time and Date is a must• Identity and observation of the
interviewer• Instructions for filling up should be in
the questionnaire, but in a different style to enable differentiation
• More important More important for mail, web questionnaires- appearance act as the persuader
• Add a cover letter for mail surveys; end with a thanks 17ICFAI University, 22nd Jan 2015
Pilot Survey is a must because.....• On a small scale, carried out prior to
the main survey• To gain information to improve the
efficiency of the main survey • Test a questionnaire• Ascertain the time taken by field
procedure • Determine the most effective size of
sampling unit• Save financial resources because if
errors are found in the questionnaire or interview early on, there would be a lesser chance of unreliable results
• Also called “Exploratory survey” in special circumstance when little is known about the material or domain under inquiry.
The main objective - determine
whether conducting a large-scale
survey is worth the effort18ICFAI University, 22nd Jan 2015
Post Script• Random & Purposive Sampling are not
rivals, rather they are complementary– Multi-stage Sampling
• Physical appearance of Questionnaire has to be attractive but such case is not necessary with schedule
• Data collection has to be fruitful• A survey - as good as the questions it
asks• Success of Questionnaire depends on
its design but in case of Schedule it depends on honesty & competency of Enumerator
RememberRemember- The respondents are doing you a
- The respondents are doing you a
favourfavour, so don’t act , so don’t act over-smartover-smart and pretend
and pretend
that you know a lotthat you know a lot
19ICFAI University, 22nd Jan 2015