Introduction every member of the population. The information

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.

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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.