What Is Simple Random Sampling?

In the unrestricted probability sampling design, more commonly known as simple random sampling every element in the population has a know and equal chance of being selected as a subject. Let us say there are 1000 elements in the population and we need a sample of 100. Suppose we were to drop pieces of paper in a hat, each bearing the name of one of the elements, and draw 100 or those from the hat with our eyes closed. We know that the first piece drawn will have a chance of being drawn; the next one is a chance of being drawn and so on.

In other words we know that the probability of any one of them being chosen is 1 in the number of the population and we also know that each single element in the hat has the same or equal probability of being chosen. We certainly know that computers can generate random numbers and one does not have to go through the tedious process of pulling out names from a hat.

When we thus draw the elements from the population, it is most likely that the distribution patterns of the characteristics we are interested in investigating in the population are also likewise distributed in the subjects we draw for our samples.

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