Guidelines for Impact Monitoring & Assessment in Microfinance ...

MONITORING & ASSESSMENT IN MICROFINANCE PROGRAMMES
Population
Sample Size
Less Accuracy* Greater Accuracy**
10 8 9
50 28 44
100 40 79
150 46 108
300 55 168
500 59 217
1000 63 277
1500 64 305
1800 65 316
NON-PROBABILITY AND PROBABILITY SAMPLING
The difference between non-probability and probability sampling is that non-probability
sampling does not involve random selection and probability sampling does.
With a probability sample, we know the odds or probability that we have represented
the population well. We are able to estimate confidence intervals for the statistics.
With non-probability samples, it is difficult to know whether we have represented the
population well. It is thus important to choose the best sampling method and state
the limitations and potential of the one selected.
In science, probability or random sampling methods are preferred over nonprobability
methods because they are considered to be more accurate and rigorous.
However, in applied social research, which includes impact monitoring and assessment,
there may be circumstances when it is not feasible, practical, affordable or
theoretically sensible to do random sampling. Below, we consider a wide range of
non-probability alternatives.
Non-probability sampling
We can divide non-probability sampling methods into two broad categories:
accidental and purposive. In many research contexts, we compose a sample by
asking for volunteers either in an accidental or haphazard way or by convenience
sampling. The problem with these types of samples is that we have no evidence
that they are representative of the general population we are interested in -
questioning, and, in many cases, we clearly suspect that they are not.
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* "Lesser" refers to a degree of
accuracy = + 0.10; Proportion
of Sample Size = 0.50;
Confidence Level = 90%
**"Greater" refers to a degree
of accuracy = + 0.05;
Proportion of Sample Size =
0.50; Confidence Level = 95% .