The most common type of probability sample is the **simple random sample**. In this procedure, each member of the population has an *equal* and *independent* chance of being selected from the population as part of the sample. Equal and independent are the critical terms.

-The chances are **equal** because there is no bias in the process that would cause one person to be chosen over another.

-The chances are **independent** because the choice of one person does not alter the chance of any other person being selected.

The beauty of this method is that (the vast majority of the time) it results in a sample with characteristics very close to those of the population. That is, it is free of *bias*.

Biasis present in a sample when some members of the population have a greater chance of being selected than other members.

To draw a simple random sample from a population, you need to take four basic steps: First, you must define the population from which you want to select the sample. Second, you need to list all the members of your population. Such a list is referred to as a **frame**. Third, each listed member of the population must have a number assigned to it. Lastly, you use a random criterion to select the sample you want. Traditionally, subjects were selected based on a table of random numbers. (You can find such tables in the back of any statistics text along with instructions for use).

These days, you can use a statistical package for the computer (like SPSS) to randomly select a sample for you. If you do not have the statistical software, you can find random number generators on the internet. You can flip coins, toss dice, draw names from a hat—whatever—so long as the method produces the same chance of being selected for every member of the population.

Simple random sampling identifies anunbiasedsample.

Last Modified: 02/03/2021