Introduction

To get

idea or information about a population we take a sample. sample – a part of the population that we

examine in order to gather information. It may be impossible to collect information

about every member of the population. The information from a sample is often

adequate and easier to obtain. The sampling design, the method chosen to

select the sample from the overall population, has important consequences. Poor

sampling designs can yield misleading conclusions.

Literature Review

Sampling design is a method for

obtaining a sample from a certain population.

Data can be collected by two

methods 1- census 2- sampling.

Sampling reduces the study

population to a reasonable size that reduces the expenses.

Sampling also prevent time consuming

research. It take too much time to cover the whole population so within a

reasonable time period we can complete our research. A sampling method is biased if

it systematically favors certain outcomes so sample should be valid and it can

be valid in two ways first one is accuracy and second is precision.

The sample design plans includes information

about sampling frames and their coverage, providing descriptions of the

national sample designs that included stages of sampling, probabilities of

selection, sampling units and sample sizes. The sample selection plans includes

detailed information about the processes for sample selection at each stage of

sampling. 1

General types of sampling

1.

Probability sampling

2.

Non Probability sampling

Probability Sampling

The sample is the proportion of the

population and such sample is selected from a population by means of systematic

way in which every element of population has a chance of being selected in

sample. Probability sampling involves convenience sampling, purposive sampling,

But this method is too much

expensive, time consuming and complex.

Non probability Sampling

The sample is not a proportion of

population and there is no system in selecting the sample. We can’t use the mathematics of probability to analyze the

results. Non probability sampling includes pure random sampling, systematic

sampling, stratified sampling and cluster sampling. 2 3

Errors in sampling

1.

Sampling

Errors

2.

Non

Sampling Errors

Sampling Errors

·

Faulty

sample design

·

Small

size of sample

Non Sampling Error

·

Coverage Error

·

Observational Error

·

Processing Error 2 4

Conclusion

By using a proper and suitable

sample design we can do a better research in very less time and cost with time

efficiency. By this we can get detailed and practical information about a

population. Once you know about your population, sampling frame, sampling

method and sample size you can use all that information to choose your sample.

References

1. European

communities (2008). Survey

sampling reference guidelines – Introduction to sample design and estimation

techniques Luxembourg: Office for Official

Publications of the European Communities

2.

Cochran,

W.G. (1977). Sampling Techniques, 3rd ed. New York: John Wiley &

Sons.

3.

Hansen

M.H., Hurvitz W.N. & Madow W.G. (1953). Sample survey methods and theory.

New York: John Wiley & Sons.

4.

Lessler

J. & Kalsbeek W. (eds.). 1992. Nonsampling Error in Surveys. New

York: John

Wiley

& Sons.