Data Collection Methods Profiling including Sampling Techniques Training of District Authorities and Partners Durable Solutions Assessment 6 September 2010

Choice of data collection methods What are the information needs? What are the information needs? Purpose of the data gathering? Purpose of the data gathering?

Profiling Numbers disaggregated by sex, age and locations Numbers disaggregated by sex, age and locations Covers the whole target population through estimations and sampling techniques. Covers the whole target population through estimations and sampling techniques. Wide range of socio-economic and needs related data Wide range of socio-economic and needs related data Provides a common baseline dataset Provides a common baseline dataset Scientific approach Scientific approach Collective approach Collective approach Unit of measurement is individual or household Unit of measurement is individual or household

Profiling Methodologies Quantitative methods 1- Rapid population estimation A- Aerial satellite imaging B- Flow monitoring C- Dwelling Count D- Head Count E- Counting using sampling methods 2- Household survey 3- Registration 4- Population Census Qualitative methods 1- Focus Group discussion 2- Semi-structured discussions 3- Key informant interviews

Sampling in the Humanitarian Context

Probability sampling: Sampling that uses random selection to choose units to be examined or measured “random” does not mean haphazard Household surveys generally use some form of probability sampling

simple random sampling

two-stage sampling Stage 1: clustering Stage 2: random household selection

stratified sampling Several groups – Suppose we need to interview blues and whites

stratified sampling

South Town Kelenni Filani Sabani Nanani Duuruni Wooroni Woluni Seguini Tanba Tanni Duguni Nyakelen Nyafila Nyoduru Nyasaba Nyasani Malanyi Kanyi Nyikulu Nyokoko Nyadaba Daba Malama Manyi Kabano Kamani Maba Kundugu Masadugu Masaba Masani Sama Samani Kono Wuluni Dioro Nyodioro Bamani Jiri Jakuma Tigui Tan Jama Tese Amana Jugu Fato Kini Malo Bolo Kalan Juguba Dabani Badaba Kelenba Gono Gononi 50 km. Saba Togoni Fatoni Fatoba Baji Seguiba Kabadugu Kununi Konodugu Kononi Wulu Wuludugu Wuluba

Random Site Selection Only visit villages > 25 km from main road Stratify population for livelihood groups: 1. Highland farm villages 2. Lowland farm villages 3. Fishing villages Visit four villages each group

South Town Kelenni Filani Sabani Nanani Duuruni Wooroni Woluni Seguini Tanba Tanni Duguni Nyakelen Nyafila Nyoduru Nyasaba Nyasani Malanyi Kanyi Nyikulu Nyokoko Nyadaba Daba Malama Manyi Kabano Kamani Maba Kundugu Masadugu Masaba Masani Sama Samani Kono Wuluni Dioro Nyodioro Bamani Jiri Jakuma Tigui Tan Jama Tese Amana Jugu Fato Kini Malo Bolo Kalan Juguba Dabani Badaba Kelenba Gono Gononi 50 Kms. Saba Togoni Fatoni Fatoba Baji Seguiba Kabadugu Kununi Konodugu Kononi Wulu Wuludugu Wuluba

Fishing Villages BajiDuguni Duuruni Filani Tanba Nanani Nyakelen Saba Sabani Seguiba Seguini Tanni Woluni We decide to randomly select four villages to visit

Fishing Villages 01Baji02Duguni 03Duuruni 04Filani 05Tanba 06Nanani 07Nyakelen 08Saba 09Sabani 10Seguiba 11Seguini 12Tanni 13Woluni We consecutively number the villages… …and then use the random numbers table to identify the four villages to visit.

TABLE OF RANDOM NUMBERS

Fishing Villages 01Baji 02Duguni 03Duuruni 04Filani 05Tanba 06Nanani 07Nyakelen 08Saba 09Sabani 10Seguiba 11Seguini 12Tanni 13Woluni

Profiling stages 1. Obtain and idea of the location of the population Key informants – community base Key informants – community base Desk review Desk review 2. Mapping 3. Stratification 4. A posterior stratification (weighting if necessary)