Sampling techniques.pptx

This ppt discuss about the different sampling techniques that are used for sampling

1. SAMPLING TECHNIQUES Surya S

2. SAMPLING… Sampling is the method of studying a whole population on the basis of the study of samples drawn from it. A sample is a representative subset of a whole population. It represents the entire population in respect of the specific characteristics under investigation. Study of the sample gives information about the whole population. This is called statistical inference. Sampling involves three principal steps, namely (a) selection of samples (b) collection of information about them and (c) making inference about the whole population.

3. SAMPLING ADVANTAGES AND DISADVANTAGES It is relatively less expensive. As the number of enumerators required is less, more efficient and better trained personals can be employed and this will result in the improvement of the quality of the data. Since the number of enumerators are less, more sophisticated instruments can be used. If destructive tests are involved in the collection of information, sampling alone can be adopted. For example, in a study of the toxicity of poisonous chemicals on a particular breed of animals, census method is unacceptable. It requires the services of experts, otherwise incorrect or misleading results will be obtained. In this method, selection of appropriate methods of sampling is necessary. In case the units of population are spread over a large area, this method cannot be used. In case the size of samples is small, sampling does not provide true representation of the population.

4. sampling techniques Sampling techniques are of mainly two types Random/Probability sampling and Non Random/Non Probability sampling Random sampling Here, the selection of sample units is absolutely a matter of chance or probability. For this reason it is also termed chance selection or probability sampling. It is the most commonly used sampling method. In it every member of the population has an equal chance of being selected. Advantages of random sampling ( i ) It does not require detailed information about the population for its effectiveness (ii) It provides estimates which are essentially unbiased and have measurable precision (iii) Evaluation of the relative efficiency of various sample designs is possible only when probability sampling is applied.

5. Methods of random sampling There are two main kinds of random sampling, namely simple or unrestricted random sampling and restricted random sampling. Simple random sampling : This is the random sampling method in which all items of the population get an equal chance of being included in the sample. The selection is free from personal bias. To ensure randomness of selection, either the lottery method or table of random numbers is used. a) Lottery method: This is the random sampling method in which all the items of a population are numbered or named on identical paper slips and then such slips are randomly selected in lots. Selection is blind fold with replacement until the desired number of units are obtained. b) Tables of random numbers: These are tables that consist of a sequence of randomly chosen digits from 0 to 9,arranged in the form of all possible combinations. Each digit has a probability of 0.1 to appear in a particular position. So, approximately equal frequencies of all combinations may be obtained. Tables of random numbers can be used to select units at random from a population.

6. Lottery method

7. Restricted random sampling: This is the type of random sampling in which certain restrictions are imposed while sampling. There are mainly three types under this, stratified sampling, systematic sampling and multistage sampling Stratified sampling: The population is first divided into homogenous groups called strata, then a specific number of random samples drawn from each stratum, and finally all the samples thus selected pooled together. E.g. one sample at random from each plot of a field.

8. Systematic sampling: systematic random sampling is also called quasi random sampling. Here the population is arranged in order, the first item is selected at random and further items are selected at specified intervals.

9. Multi-stage sampling or cluster sampling: This is the sampling procedure carried out in several stages. In this case the population is divided into several groups, called clusters, and a desired sample is selected from them to represent the whole population. In multi-stage sampling the population is first divided into several first level sampling units. From them first stage samples are obtained by a suitable method. Then, each sampling unit is divided into second level sampling units and from them second stage samples are obtained. In this manner further samples may be obtained, if necessary.

10. Non-random sampling Non-probability sampling is defined as a sampling technique in which the researcher selects samples based on the subjective judgment of the researcher rather than random selection It is a sampling method in which not all members of the population have an equal chance of participating in the study Advantages of non-random sampling Non-probability sampling is most useful for exploratory studies like a pilot survey (deploying a survey to a smaller sample compared to pre-determined sample size). Researchers use this method in studies where it is impossible to draw random probability sampling due to time or cost considerations.

11. Judgement sampling: Here the choice of sample items depends exclusively on the discretion of the investigator. The investigator uses his judgement in the choice and includes those items in the sample which he thinks are most typical of the universe with regard to the characteristic under investigation. Convenience sampling: In this, each units are selected only for convenience. A unit selected in this way is called a chunk. The results obtained following convenience sampling can hardly be representative of the population. They are generally biased and unsatisfactory. It is often used for making pilot studies.

12. Quota sampling: Here, quotas are set up according to some specific characteristics, such as so many in each of several flower colour groups, so many in each duration group, etc. There are two types of quota sampling methods 1) Controlled Quota Sampling: If the sampling imposes restrictions on the researcher’s/Statisticians choice of sample, then it is known as controlled quota sampling. In this method, the researcher can be able to select the limited samples. 2) Uncontrolled Quota Sampling: If the sampling does not impose any restrictions on the researcher’s/Statisticians choice of sample, then it is known as uncontrolled quota sampling. In this process, the researcher can select the samples of their interest.

13. Snowball sampling: Snowball sampling is where research participants recruit other participants for a test or study. It is used where potential participants are hard to find. It’s called snowball sampling because (in theory) once you have the ball rolling, it picks up more “snow” along the way and becomes larger and larger