National Information and Communication Technology Survey 2010
Sample Frame, Households [sf/hh]
In researching ICT penetration rates of a country, it is necessary to look at the target population demographic characteristics that facilitate use, access and ownership of the ICT facilities and equipments. As such, the ICT survey sought information on the general characteristics of the sampled population, including composition by age and sex, household size, education, employment, literacy, disability and source of electricity to households.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The survey was distributed into four domains, namely:
2. Major Urban areas,
3. Other Urban areas, and
4. Rural areas.
Producers and sponsors
Kenya National Bureau of Statistics
Communication Commission of Kenya
Stratified Sample methodology
Owing to the some logistical challenges the following clusters were partially or not covered at all:
• One cluster in Tana River due to floods.
• Two clusters in Molo where households shifted to safer areas after the Post Election Violence (PEV). As a result, fewer than the expected households were covered.
• One cluster in Koibatek was covered halfway due to relocation of households to pave way for a large plantation.
Weights were developed to account for the selection probabilities using the NASSEP IV sampling frame
Dates of Data Collection
Data Collection Mode
As a matter of procedure initial manual editing was done in the field by the RAs. The supervisors further checked the questionnaires and validated the data in the field by randomly sampling 20 per cent of the filled questionnaires. After the questionnaires were received from the field, an office editing team was constituted to do office editing.
Data was captured using Census and Survey Processing System (CSPRO) version 4.0 through a data entry screen specially created with checks to ensure accuracy during data entry. All questionnaires were double entered to ensure data quality. Erroneous entries and potential outliers were then verified and corrected appropriately. A total of 20 data entry personnel were engaged during the exercise.
The captured data were exported to Statistical Package for Social Sciences (SPSS) for cleaning and analysis. The cleaned data was weighted before final analysis. The weighting of the data involved application of inflation factors derived from the selection probabilities of the EAs and households detailed in section 2.2.7, on weighting the Sample Data.
Director General of KNBS
DDI Document ID
Kenya National Bureau of statistics
Ministry of Planning, National Development and Vision 2030