Some Survey Basics Random Sampling Overview If you are collecting data on a large group of people (called a "population"), it is not necessary to survey the entire population to achieve accurate results. Instead, you can gather feedback from a random, smaller number of people and draw conclusions about how the entire population would respond. This is exactly what political pollsters do - they ask a group of people a list of questions and based on their results, they draw conclusions about the population as a whole with those often heard disclaimers of "plus or minus 5%."

If you are simply looking at one large group of people as a whole, the process of determining a random sample is pretty straightforward. You will need to know how many people are in the entire group and how "accurate" you want your results to be (see "Statistical Confidence" below). Anytime you survey a portion of a population, there will be some margin of error in the results, but when the margin of error is just a few percentage points, it often becomes of little concern.

If your population consists of just a few hundred people, you might find that you need to survey almost all of them in order to achieve the level of accuracy that you desire. As the population size increases, the percentage of people needed to achieve a high level of accuracy decreases rapidly.

In other words, to achieve the same level of accuracy:

Larger population = Smaller percentage of people surveyed
Smaller population = Larger percentage of people surveyed

Extended Sampling More often than not, you will want to not only examine the results from the overall population, but also understand the differences between key demographic subgroups within the population. For example, you might want to understand the differences between males and females or senior managers and regular employees. If you plan to look at distinct subgroups such as these, you should perform an extended random sample. The process is slightly more time consuming and will require you to survey a greater number of people overall, but this technique can be very valuable.

Statistical Accuracy

In order to understand random sampling, you need to become familiar with a couple of basic statistical concepts.

1. Error - This is that "plus or minus X%" that you hear about. What it means is that you feel confident that your results have an error of no more than X%.

2. Confidence - This is how confident you feel about your error level. Expressed as a percentage, it is the same as saying if you were to conduct the survey multiple times, how often would you expect to get similar results.

These two concepts work together to determine how accurate your survey results are. For example, if you have 90% confidence with an error of 4%, you are saying that if you were to conduct the same survey 100 times, the results would be within +/- 4% of the fist time you ran the survey 90 times out of 100.

If you are not sure what sort of error you can tolerate and what level of confidence you need, a good rule of thumb is to aim for 95% confidence with a 5% error level.

Determining the "Correct" Sample Size
Determining the "correct" sample size requires 3 pieces of information

1. The size of your population
2. Your desired error level (e.g. 5%)
3. Your desired level of confidence (e.g. 95%)

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