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  1. Internal Staff

    Evaluation Option

    Conducting an evaluation using staff from the implementing agency rather than hiring external consultants.

  2. Peer review for meta-evaluation

    Evaluation Option

    Reviewing the evaluation by using peers from within the organisation or outside of the organisation

  3. Community

    Evaluation Option

    The community, particularly intended beneficiaries of an intervention, can undertake an evaluation or contribute to a combined team.

  4. Public Consultations

    Evaluation Option
    People on village meeting by public domain images

    Public consultations are usually conducted through public meetings to provide an opportunity for the community to raise issues of concern and respond to options.




  5. Simple Random Sampling

    Evaluation Option
    Geneva Crowd photo by Andy Carvin

    A simple random sample (SRS) is the most basic probabilistic option used for creating a sample from a population. Each SRS is made of individuals drawn from a larger population (represented by the variable N), completely at random. As a result, said individuals have an equal chance of being selected throughout the sampling process. The benefit of SRS is that as a result, the investigator is guaranteed to choose a sample which is representative of the population, which ensures statistically valid conclusions.

  6. Stratified Random Sampling

    Evaluation Option
    Bubblegum By Krystle Fleming

    Stratified random sampling is a probabilistic sampling option. The first step in stratified random sampling is to split the population into strata, i.e. sections or segments. The strata are chosen to divide a population into important categories relevant to the research interest.

  7. Sequential Sampling

    Evaluation Option
    Inside Purple Flower by Frank Starmer

    Sequential sampling is a non-probabilistic sampling technique, initially developed as a tool for product quality control.  The sample size, n, is not fixed in advanced, nor is the timeframe of data collection.  The process begins, first, with the sampling of a single observation or a group of observations.  These are then tested to see whether or not the null hypothesis can be rejected.  If the null is not rejected, then another observation or group of observations is sampled and the test is run again.  In this way the test continues until the researcher is confident in his or her results.

  8. Outlier Sampling

    Evaluation Option
    Humla, a basalt outlier Photo by George Brown

    This type of sampling focuses on the extremes – the end-points of the normal distribution bell-curve. Outlier sampling studies cases that are unusual or special in some way, such as outstanding successes or notable failures. Many programs can have ‘best’ sites of implementation. Studying why these sites are different can provide insight into both what is unique to that case and also what is typical and shared with other sites.

  9. Maximum Variation Sampling

    Evaluation Option
    Photo by Scuola di Atene

    A maximum variation sample contains cases that are purposefully as different from each other as possible. This type of sampling is useful for examining range in large national or global programs.

  10. Homogenous Sampling

    Evaluation Option
    Banda Aceh, Sumatra, Indonesia (Feb. 12, 2005)

    Homogenous sampling involves selecting similar cases to further investigate a particular phenomenon or subgroup of interest. The logic of homogenous sampling is in contrast to the logic of maximum variation sampling.