1. Survey Training Pack Session 7 – Basic Principles of Sampling

2. Purpose of session  Important to understand concepts underpinning sampling in order to design smart strategies – There is no recipe book that you can follow in order to design a sampling strategy – Important to reflect on your study objectives and understand how it impacts your sampling strategy Any sampling strategy is designed according to: – Study objectives/KEY indicator of interest – only 1 indicator – Variability of your study population vis-à-vis primary study objective – Resources available

3. Key definitions In small groups, take 15 minutes to develop definitions for the following concepts: – Sample – Unit of analysis – Study population – Stratification – A sample which is statistically representative

4. Sampling strategies In any sampling strategy, the units are selected RANDOMLY and not on the basis of personal preferences There are different types of sampling strategies: – Simple random sampling – Multi-stage sampling If probabilities are known and non-zero – no need for the sample to be equal; probabilities can be adjusted using sample weights – Sample weights: how many households does this surveyed household represent? Function of # of villages in sampling frame and # of households in the given village

5. Sample weights VILLAGE HOUSEHOLD RICE FARMER How many rice farmers does one surveyed rice farmer represent? Function of the number of villages in study population, number of households in each given sampled village and number of rice farmers in each given household.

6. Where do you start? What is your PRIMARY study objective/KEY indicator? 1.Are you interested in knowing the average rice yield for Lindi and Mtwara Regions for the current rainy season? 2.Or do you wish to compare the average rice yield between Lindi and Mtwara Regions for the current rainy season? The 1 st objective implies a different sampling strategy to the 2 nd objective.

7. Many study objectives A sampling strategy is developed on the basis of ONE indicator; in reality, one survey can be used to measure a list of indicators: – What is your primary objective/key indicator? This is one you use to inform your sampling strategy. – What are your secondary objectives? First, define your study population: – One or many sampling units? – Inclusion and exclusion criteria?

8. What about size? Many factors need to be taken into account: – VARIABILITY OF YOUR STUDY POPULATION vis-à-vis your study objectives – Conditions affecting the fieldwork – Data analysis plan and utility of the information required – Resources available The size of a sample influences two parameters: – Precision levels of your estimate – Confidence level

9. Confidence You have 5% chance that your sample yields the wrong estimate If you drew 20 samples out of your study population, 19 samples (i.e. 95%) would yield an estimate which captures the true estimate for the population VALUE OF ESTIMATE FOR THE STUDY POPULATION

10. Precision The 1 st sample yielded an estimate which is more precise LARGE SAMPLE SIZE SMALL SAMPLE SIZEIncrease in sample size does not necessarily imply a proportional increase in precision

11. Summary A sampling strategy is developed on the basis of ONE indicator Any sampling strategy is designed according to: – Study objective/KEY indicator of interest – only 1 indicator – Variability of your study population vis-à-vis primary study objective – Resources available Increase in sample size does not necessarily imply a proportional increase in precision and/or confidence levels – Depends on the variability of your study population