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Designing ICT Surveys:
An Introduction to the Basic Theory
Phillippa Biggs, Economist, ITU
MCIT, Cairo, Egypt
10 March 2009
Agenda
1. Objectives
2. Basic Statistical Theory
- The Basic Problem: Samples & Populations
- Sampling Sizes
- Sources of Error
3. Survey Process & Standard Sampling Techniques
4. Developing ICT Surveys for Egypt
5. Partnership on Measuring ICT for Development
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Survey Objectives
1. To investigate variable(s) from a
population of interest
2. To get an accurate, ‘representative’ &
reliable profile of the target population
3. To compare statistics with other groups
or countries
4. To be compatible or consistent with other
surveys (e.g. Europe’s eEurope+ plan).
5. To Save Money!
3
The Central Problem in Statistics
The relationship
f(m)
between the known
statistics of the sample
& the (unknown)
n3
parameters of the
population from
which it is drawn
n2
n1
Prob. distribution of
the population
Frequency distributions
of randomly drawn
samples
n4
m1
m2
m3 m0
m4
x
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Sampling Sizes
The larger the sample, the more representative it is
Use sampling distributions to choose sampling size n
f(m)
The power of a test is
influenced by:
n3
m1
• Sample size n
s
m2
• Pop std deviation s0
s
n2
n1
• Difference between
means mn and m0
m3 m0
s
x
5
Sources of Error in Surveys
1. Sampling error
2. Bias - repeated inaccuracy in estimation
(e.g. from omitted variables)
3. Manual error
(2) and (3) can be reduced with experience
and careful choice of statistical test;
(1) Inherent to surveys – need to think about
sampling error from the start!
6
The Trade-off of Any Survey
COVERAGE
COST
e.g. Census = total population
e.g. Survey = Sample
+ Complete knowledge
+ Should be more accurate!
+ Cheaper
+ Faster & more up-to-date
- BUT Expensive!
- Time-consuming
- Results may be outdated
- BUT Accuracy??
- Introduces sampling error &
potential for mistakes
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Survey Process
E.g. ICT Use in Egypt
1. Select population & 1. Urban/rural
use of ICTs
variable(s) of interest
2. Sample towns;
2. Select a sample
Sample households.
3. Choose technique
3. Collect data
4. Analyze sample to 4. Choose a suitable
test for analyzing rural
derive information
& urban differences in
about popul’n
ICT use
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Standard Sampling Techniques
1.
2.
3.
4.
5.
Random sampling
Systematic random sampling
Stratified sampling
Cluster sampling
Quota sampling
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Random Sampling
Every sample has equal probability of being chosen;
Every member of every sample has equal probability
of being chosen
+ Likely to be representative
- But it may not be representative!
- Number of possible samples increases
rapidly with sample size n
- So it can be time-consuming & tedious
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Systematic Random Sampling
Systematic sampling interval with a random start
+ Can produce more representative samples
+ Quicker & easier
- Can be much less representative!
- Hazardous, if there are regularities in
population
-Does not always produce samples of equal size
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Stratified Sampling
Members listed in order according to related variable
At least one member selected from every stratum
+ Can reduce variation & sample more likely
to be representative
+ Reduced sampling error
- Need some knowledge of population for
ordering
- Error can be increased, if one stratum is
neglected.
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Cluster Sampling
Population broken down into cross-section of areas
& Sub-samples within a random selection of areas
+ Cut costs by reducing travel for limited areas
+ Make sample more rep. while saving $
- Clusters must be representative of population
for reliable results – some knowledge of
population needed
- Increases sampling error cf random sampling,
so sample sizes may need to be increased
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Quota Sampling
Interviewers allocated a quota to survey
+ Do not need a survey frame of population
+ Small sample sizes, quick & economical.
- BUT dubious, as it assumes prior knowledge
of population.
- Introduces error, but cannot quantify error.
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ICT Surveys for Egypt
1. Access to and use of ICTs strongly correlated
with income, socioeconomic class, area &
education.
2. Need to take account of income to ensure not
implicitly measuring socio-economic class; but at
the same time, suitable variable for stratification.
3. The Partnership on Measuring ICT for
Development has developed a Manual on ICT
Household Statistics.
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Partnership on Measuring
ICT for Development
• Multi-stakeholder partnership launched in June 2004 to identify a
core set of ICT indicators and to help guide countries in collecting
and disseminating ICT statistics:
- basic ICT infrastructure & access indicators;
- household and individual indicators;
- Indicators on use of ICT by businesses.
• Divided into core & extended core ICT indicators.
• ITU Manual on ICT Household Statistics;
• UNCTAD Manual on the Information Society.
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Thank you
[email protected]
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