Optimize! Optimize! Minimize Sample Size, Maximize Data Quality

A good quality data is generated in the following manner.

1.       A clear objective of study

It should answer following questions.

a.       What we do we want to study?

b.      How we want to study?

c.       What questions (related to the study) should be addressed?

d.      How to address these questions?

Answering these questions requires knowledge in the subject. These questions bridge that subject (say Medicine or Engineering) to statistics. We collect quantitative facts that validate the theory. This theory is the object of our study. 1c, 1d discussed above is an art in itself. It can also be called an art of questionnaire design.

2.         A representative sample

This sample should represent the entire cross section of the population with respect to the objective of study. A sample is a small replica of the population. Here all the features of the population are reflected in the sample in right proportions. A sample is a smaller version of the population.

For example if we are interested in testing the efficacy of medicine A, this medicine should be a administered to a sample comprising of entire cross section of age groups that consume this medicine. This cross section should represent the population.  

3.  Design of Experiments based on principles of randomization, replication and local control.

These principles ensure that the data are collected with minimum background noise. It can be metaphorically linked to tuning of a radio. If we are at the right frequency we get clear radio messages with minimum white noise. A well designed experiment ensures that we can clearly hear the message conveyed by the data with minimum background noise.