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Proposed definitions will be considered for inclusion in the Economictimes.com Definition: Random sampling is a part of the sampling technique in which each sample has an equal probability of being chosen. A sample chosen randomly is meant to be an unbiased representation of the total population. If for some reasons, the sample does not represent the population, the variation is called a sampling error. Description: Random sampling is one of the simplest forms of collecting data from the total population. Under random sampling, each member of the subset carries an equal opportunity of being chosen as a part of the sampling process. For example, the total workforce in organisations is 300 and to conduct a survey, a sample group of 30 employees is selected to do the survey. In this case, the population is the total number of employees in the company and the sample group of 30 employees is the sample. Each member of the workforce has an equal opportunity of being chosen because all the employees which were chosen to be part of the survey were selected randomly. But, there is always a possibility that the group or the sample does not represent the population as a whole, in that case, any random variation is termed as a sampling error. An unbiased random sample is important for drawing conclusions. For example when we took out the sample of 30 employees from the total population of 300 employees, there is always a possibility that a researcher might end up picking over 25 men even if the population consists of 200 men and 100 women. Hence, some variations when drawing results can come up, which is known as a sampling error. One of the disadvantages of random sampling is the fact that it requires a complete list of population. For example, if a company wants to carry out a survey and intends to deploy random sampling, in that case, there should be total number of employees and there is a possibility that all the employees are spread across different regions which make the process of survey little difficult.
Probability sampling is based on the fact that every member of a population has a known and equal chance of being selected. For example, if you had a population of 100 people, each person would have odds of 1 out of 100 of being chosen. With non-probability sampling, those odds are not equal. For example, a person might have a better chance of being chosen if they live close to the researcher or have access to a computer. Probability sampling gives you the best chance to create a sample that is truly representative of the population. As a rule of thumb, your sample size should be over about 30. If you have a small sample, you may need to try one of the non-probability sampling techniques instead. Watch the video for an overview of probability sampling: Probability Sampling Methods Can’t see the video? Click here.
Advantages and DisadvantagesEach probability sampling method has its own unique advantages and disadvantages. In general, probability sampling minimized the risk of systematic bias. This means that you are reducing the risk of over- or under-representation--ensuring your results are representative of the population. Using probability sampling also means that you can use statistical techniques like confidence intervals and margins of error to validate your results. Advantages
Disadvantages
ReferencesCook, T. (2005). Introduction to Statistical Methods for Clinical Trials (Chapman & Hall/CRC Texts in Statistical Science) 1st Edition. Chapman and Hall/CRC ---------------------------------------------------------------------------
 Need help with a homework or test question? With Chegg Study, you can get step-by-step solutions to your questions from an expert in the field. Your first 30 minutes with a Chegg tutor is free! Comments? Need to post a correction? Please Contact Us. What type of probability sampling in which each element of the population has an equal chance of being selected?Simple random sampling. In simple random sampling (SRS), each sampling unit of a population has an equal chance of being included in the sample.
Which of the following is the probability method of selecting samples from a population?Major probability sampling methods are simple random sampling, stratified random sampling, and Cluster sampling, and Systematic sampling.
What is equal probability sampling?Sampling which results in each person having the same chance of being selected is termed equal probability of selection method (EPSEM) sampling.
What type of probability sampling is considered as the best type of sampling?Simple random sampling: One of the best probability sampling techniques that helps in saving time and resources, is the Simple Random Sampling method. It is a reliable method of obtaining information where every single member of a population is chosen randomly, merely by chance.
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