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Sampling Theory

Sampling is statistics is used to select a subset of individuals for the whole population in order to get sample of the whole population. These ideas and assumptions are then used for making predictions which are based on statistical inference. Each observation is used to measure one or more properties of observable bodes which are distinguished as independent individuals or objects.

The process of the sampling prices proceeds as-

1. The defining of the population of concern

2. Specification of the sample frame

3. Specification of a sampling method

4. Implementation of the sampling plan

5. Data collection and sampling

The population of sampling- for successful statistical practice, the defined problem must be focused upon the population from which the sample is drawn. The population can be defined as having all people or items with the desired characteristic of study or understanding.

The sampling frame- by the use of sampling frames, all the elements can be identified and included in the sample. The telephone directory can be said to be a most straightforward type of frame used in a opinion poll, which has a list of element of the population(sometimes entire population), with the contact information.

Probability sampling- the sampling in which every unit of the population gets the chance to be selected in the sample is called probability sampling. This probability can also be very accurately determined.

Non probability sampling- in this type of sampling, some elements of the population do not get the chance of being selected in the swampland and thus the probability of selection cannot be accurately determined.

Simple random sampling- for a given size, all subjects of the frame are given an equal probability. Each element of the frame thus gets an equal probability for selection and the frame cannot be portioned or subdivided. All pairs of elements get equal chance of selection.

Systematic sampling- the selection of elements is done at regular intervals of the ordered list by arranging the target population as pr the ordering scheme.

Stratified sampling- when the population embraces a number of distinct categories, the sampling frame is categorized into ‘strata’ which are separate from each other. The selection of individual elements is done by random selection of the samples from the independent sub population.

Cluster sampling-it is a cost effective approach towards sampling when the respondents are selected in groups or clusters. In this type of sampling method, the sampling is often clustered on the basis of time periods or geography.

Matched random sampling- in this method of sampling, the participants are assigned to groups where the pairs of participants are first matched on the basis of some characteristic and then are assigned individually and randomly to various groups.

Quota sampling- here the population is segmented into mutually exclusive sub groups and then is judged in order to select the units or subjects from each segment in a specified proportion.

Convenience sampling- it is a type of non probability sampling method where the samples are drawn form the population which are close to hand. In other words, the selection of sample is on the basis of its readily availability and convenience.

Line intercept sampling- it is that method of a region where an element is sampled when the chosen line segment or transect intersects the segment.

Panel sampling- in this method, a group of participants is selected through random sampling method and then these groups are asked about information repeatedly in a given time frame. Each participant is then given the same survey or interview on two or more different time intervals and each period of data collection is termed as ‘wave’.

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