SIMPLE RANDOM SAMPLING
The death of one man is a tragedy. The death of millions is a statistic. — Joseph Stalin
The objective of an sample survey is to make inference about the population parameter from the information contained in a sample.
The two factors affecting the quality and quantity of information contained in a sample are
i. Representativeness of the sample
ii. Sample size
Let us consider the sales of mobilephones. And with the help of the same example we can discuss how important the afforementioned factors are when sampling is considered.
i. The representativeness of a sample can be controlled by controlling the way of selecting the sample. Now we consider only the sales of mobilephones on a record of only considering buyers from Kolkata, Mumbai and Delhi. So if we compare this result to the insights we received while considering all the states equally, we’ll notice a huge difference in result.
The procedure of selecting a sample is known as sample survey design.
ii. For fixed sample size n, we will consider various sampling designs or sampling procedures for selecting representative sample. for example, the insight developed from say 10 selfie-addicts buying the newest model and that of a regular day of sale where we are receiving hundreds of buyers from different origins are different.
What is SIMPLE RANDOM SAMPLING?
If a sample of size n is drawn from a population of size N in such a way that each and every member of the population has equal chance of being selected in the sample, then the sampling is called Simple Random Sampling.
The sample thus obtained is called a Simple Random Sample.
In simple random sampling every possible sample of size n has also equal chance of being selected .
Now, this random sampling may occur with replacement or without replacement.
- Simple Random Sampling With Replacement (SRSWR)
- Simple Random Sampling Without Replacement (SRSWOR)
In simple random sampling every possible sample of size n has also equal chance of being selected .
In a simple random sampling, if the drawings are made one by one and each selected item is returned to the population before the next drawing, then the sampling procedure is known as Simple Random Sampling With Replacement (SRSWR)
In a simple random sampling, if the items are not returned to the population before the next drawing, then the resulting sampling procedure is known as Simple Random Sampling Without Replacement (SRSWOR)
Random sampling ensures that results obtained from a sample should approximate what would have been obtained if the entire population had been measured. The simplest random sample allows all the units in the population to have an equal chance of being selected. It’s simplicity and lack of bias adds to it’s major advantages.
Amongst the disadvantages are it’s difficulty in gaining access to a list of a larger population , time , costs and that bias can still occur under certain circumstances
REFERENCE:
1. Mathematical Statistics by S.K. DE and S. Sen (by U.N Dhur and Sons Private Limited)
2. An Introduction to Probability and Statistics by Md Ismail Hoque (by Techno World)
3.Fundamentals of Mathematical Statistics by S.C. Gupta and V.K. Kapoor (by Sultan Chand & sons)
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