INTRODUCTION TO ECONOMETRICS II
ECO 306
NOUN
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ii.
Greater speed: for the same reason the data can be collected and summarized more quickly with a sample than with a complete count. This is a vital consideration when the information is urgently needed.
iii.
Greater Scope: a complete census is impracticable the choice lies between obtaining the information by sampling or not at all. Thus surveys that rely on sampling have more scope and flexibility regarding the kind of information that can be obtained.
iv.
Greater Accuracy: here, personnel of higher quality can be employed and given intense training. This would allow for much more careful supervision of the fieldwork. Processing and analysing of the results become feasible because the volume of work is now reduced. The sample would most likely produce amore accurate result than the complete enumeration.
1.1.3.4.3 Types of sampling technique
i.
Probability sampling technique: Simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, etc.
ii.
Non-probability sampling technique: Snowball sampling, quota sampling technique, accidental or convenient sampling technique, etc. Sample designs that utilise planned randomness are calledprobability sampleswhile non-probability doesn‟t apply randomness as it is based on the subjective dictate of the researcher since all elements are not given equal chance of being selected. The most fundamental probability sample is the simple random sample. Ina simple random sample, a sample of n sampling units is selected in such away that each sample of size n has the same chance of being selected. In practice, other more sophisticated probability sampling methods are commonly used, but we would focus hereon simple random sampling technique.
1.1.3.4.4 Simple Random Sampling technique
Suppose the observations
,
are to be sampled from a population with mean, standard deviation, and size N in such away that every possible sample of size n has an equal chance of being selected. Then the sample
,
was selected in a simple random sample. If the sample mean is denoted by
̅ then we have
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