Non – Probability Sampling (Convenience, Purposive).

Non – Probability Sampling (Convenience, Purposive).

1. NON – PROBABILITY SAMPLING (CONVENIENCE, PURPOSIVE).

2. Sampling is the act, process, or technique of selecting a representative part of a population for the purpose of determining parameters or characteristics of the whole population. INTRODUCTION

3. Sampling is concerned with the selection of a subset of individuals from population to estimate characteristics of the whole population. Sampling is a process of collection of data Sampling is a good representative of the population. MEANING OF SAMPLING

4. W. G. Cocharn : “ In every branch of science we lack the resources, to study more than a fragment of the phenomena that might advance our knowledge”. In this definition, a ‘fragment’ is the sample and ‘phenomena’ is the ‘population’. The sample observation are applied to the phenomena, i.e. generation. David S. Fox: “ In the social sciences, it is not possible to collect data from every respondent relevant to our study but only from some fractional part of that respondents. The process of selecting, the fractional, part is called sampling. ‘Sampling design’ means the joint procedure of selection and estimation. Sampling should be such that error of estimation is minimum . DEFINITION OF SAMPLING:

5. The sampling method was used in social sciences research as early as in 1754 by A.L Bowley . When the population is very large, it can be satisfactorily covered through sampling. It saves a lot of time energy and money. Especially when the units of an area are homogeneous, sampling techniques is really useful. When the data are unlimited, the use of this method is really useful. When cent percent accuracy is not required, the use of this technique becomes inevitable. When the number of individuals to be studied is manageable intensive study becomes possible. IMPORTANT OF SAMPLING

6. Characteristics of a Good Sample True representative Free from bias Objective Accurate Comprehensive Economical Approachable. Good size Feasible Practical

7. ADVANTAGES OF SAMPLING Reduced cost: It is economical. Greater Speed: Sampling is less time consuming than the census technique. Greater Scope: It has great scope and flexibility. Greater Accuracy: Sampling ensure high degree of accuracy due to a limited area of operation . DISADVANTAGES OF SAMPLING Less Accuracy: Conclusions derived from sampling are more liable to error. Changeability of units: Difficulties in selecting a truly representative sample: The results of a sample are accurate and usable only when the sample is representative of the whole group. Need for specialized knowledge: Sampling method requires a specialised knowledge in sampling technique statistical analysis and calculation of probable error.

8. TECHNIQUES OF SAMPLING Probability sampling techniques. Non – probability sampling techniques . Probability sampling techniques: Probability sampling is a sampling technique wherein the samples are gathered in a process that gives all the individuals in the population equal chances of being selected . According to G. C Halmstadter , “A probability sample is one that has been selected in such a way that every element chosen has a known probability of being included.

9. TECHNIQUES OF PROBABILITY SAMPLING Simple random sampling. Systematic sampling. Stratified sampling Multiple or double sampling Multistage Sampling Cluster sampling.

10. NON – PROBABILITY SAMPLING Non – probability sampling is a sampling technique where the samples are gathered in a process that does not all the individuals in the population equal chances of being selected . In the absence of any idea of probability the method of sampling is known as Non – probability sampling.

11. Characteristics of Non – Probability Sampling There is no idea of population. There is no probability of selecting any individual. In has free distribution. The observations are not used for generalisation purpose. Non – parametric or non – inferential statistics are used. There is no risk for drawing conclusions.

12. Types of Non – Probability Sampling Convenience sampling Purposive sampling Quote sampling Incidental sampling Snowball sampling.

13. Convenience Sampling This is also known as ‘accidental’ or “haphazard” sampling Sample is selected according to the convenience of the sample. No pre – planning is necessary for the selection of items. The convenience may be in respect of availability of source list, accessibility of the units, etc.

14. EXAMPLES OF CONVENIENCE SAMPLING The researcher engaged in the study of university students might visit the university canteen, library, some departments, play ground, verandahs and interview certain number of students . A nother example is of election study. During election times, media personnel often present man – on – the – street interviews that are presumed to reflect public opinion. In this sampling representativeness is not significant.

15. MERIT OF CONVENIENCE SAMPLING Convenience sampling is quick and economical. Convenience sampling are best utilised for exploratory research when additional research with subsequently be conducted with a probability sample. A convenience sampling may be used in any one or more cases when the universes is not clearly defined .

16. DEMERIT OF CONVENIENCE SAMPLING It is unscientific. It is a biased sampling method. Sampling unit is not clear. A complete source list is not available.

17. PURPOSIVE SAMPLING This sampling method is also known as judgemental sampling. Appropriate characteristic required of the sample members. Sampling is possible only when there is a specific objective. This method need not be used when there are multi – purpose objectives involved in the study. The investigator has to pick up only such sample which is relevant to his study. The investigator should possess full knowledge of the universe.

18. EXAMPLES OF PURPOSIVE SAMPLING Suppose , the researcher wants to study beggars. He knows the three areas in the city where the beggars are found in abundance. He will visit only these three areas and interview beggars of his choice and convenience . Popular journals conduct surveys in selected metropolitan cities to assess the popularity of politicians and political parties or to forecast election results.

19. MERITS OF PURPOSIVE SAMPLING It uses the best available knowledge concerning the sample subjects. It give better control of significant variables. In it sample group data can be easily matched. In it there is homogeneity of subject used in the sample.

20. DEMERITS OF PURPOSIVE SAMPLING In it the reliability of the criterion is questionable. In it the knowledge of population is essential. In is there may be errors in classifying sampling subjects. It is unable to utilise the inferential parametric statistics. It is unable to make generalization convening total population.

21. CONCLUSION On the basis of sample study, we can predict and generalise the behaviour of the population . Most researchers come to a conclusion of their study by studying a small sample from the huge population or universe.