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Thursday, August 22, 2019

SAMPLING


Sampling
Sampling is a process used in statistical analysis in which predetermined number of observation is taken from larger population. The methodology used to sample from a larger population depends on the types of analysis being performed but may include simple random sampling or systematic sampling.
The way in which we select a sample of individuals to be research participants (random sampling) will determine the population to which we may generalize our research findings The procedure that we use for assigning participants to different treatment groups. (Are the groups equal on all known and unknown factors?) We address random

Probability Sampling Methods
Random Sampling Simple.  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 random sample is to give each individual in a population a number and then we use of table of random numbers to decide which individual is to include.
            As with all probability sampling method, Simple random sampling allows the sampling error to be calculated and reduce selection bias .A specific advantages is that it is the most straight forward method of probability sampling. A disadvantage of sample random sampling us that you may not select enough individuals your characteristic of interest, especially if that characteristic is uncommon. It may also difficult to define a complete sampling frame and inconvenient to contact them, especially in different forms of contact are required. (E mail, phone, post) and urn sample units are scattered over a. Whole geographical area.
 Systematic sampling.  Individuals are selected at regular intervals from the sampling frame. The intervals are chosen to ensure an adequate sampling size. If you need sample size 'n' from a population of size 'x' you should select every x/n the individual for the sampling.  Systematic sampling is often more convenient than simple random sampling, and it is easy to administer. However it may also lead to bias.   
            Stratified Sampling.   In these methods, the population is first divided into subgroups (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 subgroups. The study sample is then obtained by taking equal sample sizes from each stratum. In stratified sampling, i it may also be appropriate to choose non equal sample sizes from each stratum.  Stratified sampling improves accuracy and representativeness of the result by reducing sampling bias. However, it requires knowledge of the appropriate characteristics of the sampling frame. It can be difficult to decide which characteristics to stratify by.
 Cluster sampling.   In a cluster sample, subgroups of the population are used as the sampling, rather than individuals.  The population is divided into subgroups, known as clusters, which are randomly selected to be included in the study.
Clusters are identified and included in a sample on the basis of defining demographic parameters such as age, location, sex, etc. which makes it extremely easy for a Serve creator to derive effective inference from the feedback.
Non Probability Sampling Method
The non - probability sampling method uses the researcher's discretion of selecting a sample. This type of sample is derived mostly on the basis of the researcher or statistician’s ability to get to this sample this type of Sampling is used for primary research work the primary objective is to derive a hypothesis about the topic in research. Here each member of the population does not have an equal chance of being a part of the sample and those parameters are known only post selection to the sample.
Non probability sampling can be further classified into four distinct types of samples. They are:
Convenience sampling.   Convenience sampling is perhaps the easiest method of sampling, because participants are selected based on availability and willingness to take part. Useful results can be obtained but the results are brown to significant buyers because those who volunteered to take part may be different from those who choose not to (volunteer bias) and the sample may not be representative of other characteristics, such as age or sex.
Quota sampling.  This method of sampling is offer used by market researchers interviewers are given a quota of subjects of a specified type two attempt to recruit.  For example and interviewer might  be told to go out and select 20 adult men , 20 adult women , 10 teenage girls and 10 teenage boys so that they could interview them about their television viewing.
 Judgmental/ purposive sampling.  The judge mental / purposive sampling method is a method of developing a sample purely on the basis and discretion of the researcher purely on the basis of nature of study along with his / her understanding of the target audience .In the sampling method, people who only fit the research criteria  and objective are selected and the remaining are kept out. Also known as selective or subjective sampling this technique relies on the judgement of the researcher when choosing who to ask to participate researchers may implicitly thus choose a "representative” sample to suit their needs, or specifically approach individuals with certain characteristics.  This approach is often used by the media when canvassing the public for opinions and in qualitative research.

            Snowball sampling.  In this method is commonly used in Social Sciences then investigating hard - to - reach groups. Existing subjects are asked to nominate further subjects known to them, so the sample increases in size like a rolling snowball.


Figure no.1 Sampling
Table 1 Advantages and disadvantages of sampling

Advantages                                   Disadvantages
Low cost of sampling.
Less time consuming.
Scope of sampling is high.
Accuracy of data is high.
Organization of convenience.
Intensive and exhaustive data.
Suitable in limited resources.
Chance of bias.
Difficulties in selecting a truly representative sample.
Inadequate knowledge in the subject Changeability of units.
Impossibility of sampling.

References
v  https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1a-epidemiology/methods-of-sampling-population
v  https://www.investopedia.com/terms/s/sampling-asp
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