1. Designing ICT Surveys: An Introduction to the Basic Theory Phillippa Biggs, Economist, ITU MCIT, Cairo, Egypt 10 March 2009

2. 2 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 Agenda

3. 3 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! Survey Objectives

4. 4 The Central Problem in Statistics The relationship between the known statistics of the sample & the (unknown) parameters of the population from which it is drawn f(  ) x Prob. distribution of the population Frequency distributions of randomly drawn samples     nn nn n3n3 nn 

5. 5 Sampling Sizes The larger the sample, the more representative it is Use sampling distributions to choose sampling size n f(  ) x The power of a test is influenced by: Difference between means  n and  0 Pop std deviation   Sample size n     nn n3n3 nn   

6. 6 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! Sources of Error in Surveys

7. 7 COVERAGE e.g. Census = total population + Complete knowledge + Should be more accurate! - BUT Expensive! - Time-consuming - Results may be outdated The Trade-off of Any Survey COST e.g. Survey = Sample + Cheaper + Faster & more up-to-date - BUT Accuracy?? - Introduces sampling error & potential for mistakes

8. 8 1.Select population & variable(s) of interest 2.Select a sample 3.Collect data 4.Analyze sample to derive information about popul’n Survey Process E.g. ICT Use in Egypt 1.Urban/rural use of ICTs 2.Sample towns; Sample households. 3.Choose technique 4.Choose a suitable test for analyzing rural & urban differences in ICT use

9. 9 1.Random sampling 2.Systematic random sampling 3.Stratified sampling 4.Cluster sampling 5.Quota sampling Standard Sampling Techniques

10. 10 + 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 Random Sampling Every sample has equal probability of being chosen; Every member of every sample has equal probability of being chosen

11. 11 + 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 Systematic Random Sampling Systematic sampling interval with a random start

12. 12 + 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. Stratified Sampling Members listed in order according to related variable At least one member selected from every stratum

13. 13 + 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 Cluster Sampling Population broken down into cross-section of areas & Sub-samples within a random selection of areas

14. 14 + 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. Quota Sampling Interviewers allocated a quota to survey

15. 15 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. ICT Surveys for Egypt

16. 16 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. Partnership on Measuring ICT for Development

17. 17 Thank you phillippa.biggs@itu.int