SAMPLING PLAN

A sample design is a definite plan for obtaining a sample from a specific population. It consists of the the procedure the researcher would adopt in selecting items for the sample

The sample design determines the number of items to be included in the sample and is decided before data are gathered. There exist several sample designs from which a researcher can opt. Some designs are comparatively more precise and easier to apply than others. A researcher must select/prepare a sample design which should be reliable and representative for his research st Marketing research is based on either population (universe) enquiry or sample enquiry The researcher favoring one method over another depends on the size of the universe and the given to the research agency, Sampling may be defined as the selection of some part of an aggregate or totality on the basis of which a judgment or inference about the aggregate is taken. Simply, it is the process of learning about the population on the basis of a sample drawn from it. Thus in the sampling only a part of the universe is studied and the conclusions drawn on that basis are generalized for the entire universe
FEATURES OF SAMPLING METHOD:The sampling technique has following good features and these highlight its value and significance 

Economy: The sampling technique is economical and time saving than the census technique

. Reliability: If the choice of sample units is made with due care and the matter under survey is not heterogeneous; the conclusion of the sample survey can have almost the same reliable as that of census survey

3.     Detailed Study: Since the number of sample units is fairly small these can be studied intensively and elaborately and can be examined from multiple viewpoints.

4.             Scientific Base: This is a scientific technique because the conclusions derived from the study of certain units can be verified from other units. By taking random samples we can determine the amount of deviation from the norm.

5.             Greater Suitability in most Situations: Most of the surveys are made by the technique of sample survey, because when the matter is of a homogeneous nature, the examination of a few units suffices, as is the case in the majority of situations.

LIMITATIONS OF SAMPLING

1.             Less Accuracy: In comparison to census technique the conclusions derived from sample are more prone to error. In this respect sampling technique is as accurate as the census technique.

2.             Changeability of Units: If the units in the field of survey are liable to change or if these are not homogeneous the sampling technique will, be very dangerous.  It may not scientific to extend the conclusions derived from one set of sample to other samples, which are heterogeneous  or are changeable.

3.             Misleading Conclusions: If due care is not taken in the selection of samples or if they are arbitrarily chosen, the conclusions drawn from them may prove misleading if extended to census. For example, in evaluating the monthly expenditure of university students if we select for sample only rich students, results are likely to be highly erroneous if extended to all students.

4.             Need for Specialized Knowledge: The sample technique can be successful only if a competent and able scientist makes the selection. If an average scientist does this, the selection is liable to be wrong.

5.             When Sampling is not possible: Under certain circumstances it becomes difficult to use the sampling technique particularly once the time is very short and it is not possible to select sample, the technique cannot be used. Besides, if 100% accuracy is required and the material is of a heterogeneous nature the sampling technique cannot be used.

CHARACTERISTICS AND SIZE OF SAMPLING 

Characteristics of Ideal Sample: A good sample has following qualities:

1.           Representativeness: An ideal sample must be such that it represents adequately the entire populations. We would attempt to select those units that have the same qualities and features as are found in the whole data.  The sample should not lack in any characteristic of the population. Independence: Every unit should be available to be included in the sample.  Adequacy: The number of units included in a sample should be sufficient to enable derivation of conclusions applicable to the whole population. A sample having 10% of the whole population is generally adequate. Homogeneity: The units included in the sample must bear likeness with order units; otherwise the sample will be unscientific.

Size of Sampling: For proper study of the problem, it is necessary that the sample be of proper size.  Too small or too big, ample shall make the study difficult.  What should be the size of the sample is a question, which should be answered only after taking into account the various factors of the research problem at hand.

Factors to be considered in Sampling Size: The following issues should be pondered while deciding the sample size:

(i)            The size of the universe: The large the size of the universe, the bigger should be the sample size.

(ii)          The resources available: If the resources available are vast, a large sample size could be taken. However, in most cases resources constitute a big constraint on sample size.

(iii)         The degree of accuracy or precision desired: The greater the degree of accuracy desired the larger should be the sample size. However, it does not necessarily mean that bigger samples always ensure greater accuracy.

(iv)        Homogeneity or heterogeneity of the universe: If the universe consists of homogeneous units, a small sample may serve the purpose but if the universe consists of heterogeneous units, a large sample may be required.

(v)          Nature of study: For an intensive and continuous study, a small sample may be suitable. But for studies, which are not likely to be repeated and are quite extensive in nature, it may be necessary to take a large sample size.

(vi)        Method of sampling adopted: The size of sample is also influenced by the type of sampling plan adopted. For example, if the sample is a simple random sample it may necessitate a bigger sample size. However, in a properly drawn stratified sampling plan, even a small sample may give better results.

The above factors have to be properly weighted before arriving at the sample size. However, the selection of optimum sample size is not that simple, as it might seem to be.