Sampling Method Sampling Method Presentation By Dr M

Sampling Method

Sampling Method Presentation By Dr. M. JULIAS CEASAR Asst. Professor Department of Commerce St. Joseph’s College (Autonomous) Tiruchirappalli

Introduction • Empirical field study require collection of first hand information or data. • Types of Research: Pure and Applied Research. • Pure research (also known as “basic” or “fundamental” research) is exploratory in nature and is conducted without any practical end-use in mind. It is driven by gut instinct, interest, curiosity or intuition, and simply aims to advance knowledge and to identify/explain relationships between variables.

Applied Research • In general, applied research is not carried out for its own sake but in order to solve specific, practical questions or problems. • It tends to be descriptive, rather than exploratory and is often based upon pure research.

Sample • The aggregate of all the units pertaining to a study is called as Population or Universe. • A part of population is known as sample. • The process of drawing a sample from a larger population is called sampling. • A group that includes all the cases (individuals, objects, or groups) in which the researcher is interested. • Sample A relatively small subset from a population.

Aims of Sampling • Sampling must reflect fairly accurately the characteristics of the population. • To test Hypotheses relating to a population.

Characters of a Good Sample • • Representativeness. Accuracy. Precision Size. • ADVANTAGES OF SAMPLING: 1) It reduces the time and cost of research studies. 2) Sampling saves labour. 3) Sampling provides quicker results. 4) Sampling is the only procedure possible, if the population is infinite.

Limitations of Sampling • Sampling demands a thorough knowledge of sampling methods. • Small sample is not always good. • A Complicated sampling may require more labour. • Not possible to ensure representativeness.

• Sampling method fall into two categories: • Probability Sampling: Every individual in the population is known and each has a certain probability of being selected. A random process decides the sample based on each individual’s probability. • Non Probability Sampling: The population is not entirely known, thus individual probabilities cannot be known.

Simple Random Sampling • In this case each individual is chosen entirely by chance and each member of the population has an equal chance, or probability, of being selected. • One way of obtaining a random sample is to give each individual in a population a number, and then use a table of random numbers to decide which individuals to include.

Systematic Sampling • Individuals are selected at regular intervals from a list of the whole population. • The intervals are chosen to ensure an adequate sample size. • For example, every 10 th member of the population is included. • Ex: The Hindu CSDS Election Survey – Pre. Poll, Mid-Poll and Post-Poll survey.

Stratified Sampling • In this method, the population is first divided into sub-groups (or strata) who all share a similar characteristic. • It is used when we might reasonably expect the measurement of interest to vary between the different sub-groups

Clustered Sampling • In a clustered sample, sub-groups of the population are used as the sampling unit, rather than individuals. • The population is divided into sub-groups, known as clusters, and a selection of these are randomly selected to be included in the study. • All members of the cluster are then included in the study.

Quota Sampling • This method of sampling is often used by market researchers. Interviewers are given a quota of subjects of a specified type to attempt to recruit. • For example, an interviewer might be told to go out and select 20 adult men and 20 adult women, 10 teenage girls and 10 teenage boys so that they could interview them about their television viewing.

Convenience Sampling • Convenience sampling is perhaps the easiest method of sampling, because participants are selected in the most convenient way, and are often allowed to chose or volunteer to take part. • Good results can be obtained, but the data set may be seriously biased.

Snowball Sampling • This method is commonly used in social sciences when investigating hard to reach groups. • Existing subjects are asked to nominate further subjects known to them

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