Simple Random Sampling

[Audio] In this video we are going to see the basics of simple random sampling.

[Audio] A simple random sample is a randomly selected subset of a population. In this sampling method, each member of the population has an exactly equal chance of being selected. This method is the most straightforward of all the probability sampling methods, since it only involves a single random selection and requires little advance knowledge about the population. It uses randomization, any research performed on this sample should have high internal and external validity, and be at a lower risk for research biases like sampling bias and selection bias..

[Audio] There are two subtypes of simple random sampling, Sampling without replacement and Sampling with replacement, Sampling without replacement is a method of selection of n units out of the N units one by one such that at any stage of selection, any one of the remaining units have the same chance of being selected, Sampling with replacement is a method of selection of n units out of the N units one by one such that at each stage of selection, each unit has an equal chance of being selected.

[Audio] Here is an example on Sampling without replacement, in which only the words a b g h are used in the taken sample.

[Audio] Here is an example on Sampling with replacement, in which of all the samples include some letters of a b g h and also contains other letters in population as well.

[Audio] Step 1 is to decide on the population that you want to study, Next, you need to decide how large your sample size will be, Although larger samples provide more statistical certainty, they also cost more and require far more work, Next step can be done in one of two ways: the lottery method or random number method, After selecting your sample, you should collect data from your sample, To ensure the validity of your findings, you need to make sure every individual selected actually participates in your study.

[Audio] Simple random sampling is used to make statistical inferences about a population, It helps ensure high internal validity : randomization is the best method to reduce the impact of potential confounding variables However, simple random sampling can be challenging to implement in practice, To use this method, there are some prerequisites: You have a complete list of every member of the population, You can contact or access each member of the population if they are selected, You have the time and resources to collect data from the necessary sample size, Simple random sampling works best if you have a lot of time and resources to conduct your study, or if you are studying a limited population that can easily be sampled.

[Audio] Sampling errors occur because of variation in the number or representativeness of the sample that responds, And below are some of the ways we can control and reduce the sampling error.

[Audio] I hope this video helps you understand the basics of Simple Random Sampling, Thank you.