Why do we still teach systematic random sampling as an option?

As you may recall from your Statistics 101, simple random sampling is when you select from the sample at random. So, if you want 100 people out of a sample of 10,000 in a dataset, you would pull a random sample by, most likely, using a random number function.

In a systematic sample, you select the first number at random. Say you want 1% of the population, like our 100 out of 10,000 example. You would select a number between 1 and 100 and then you’d select every 100th person after that. So, if your number was 98, you’d select person #98, 198, 298 and so on.

The danger is always that your data may be in some sort of systematic order. For example, if you had collected students tests and entered them, you might have classes where teachers seated the students alternating boys and girls. So, you might get a whole bunch of boys or a whole bunch of girls.

Yes, systematic sampling is easier if you are pulling the data by hand,  but given that almost all samples in any real-life use are pulled by a computer, why do we even teach systematic sampling? If you have a data set already created, I can’t think of any benefit to systematic random sampling. What, it takes the computer .0015 seconds instead of .0007 seconds?

The only possible benefit I could imagine was if you were sampling people as they came through the door of a clinic or shopping mall. In that case, it might be easier to start with a person at random and then badger every Nth person.

Even that doesn’t really make sense to me, though. It seems that in those settings, you have a hard enough time getting people to stop and talk to you, you ought to just try to grab every person you can get.

Let’s say you are doing an observational study, though, of public behavior. In this case, you really could do a random sample and, theoretically, a systematic random sample would be much easier than trying to keep track of whether that person who walked by was #17 and the next was #134. Still, even this specific situation is no excuse. It would be really easy to write a program that makes your phone beep at random times, a minimum of some fixed duration apart (the time you plan on observing each person) and at each beep you could observe the person who was walking by, browsing in front of your store window, or whatever it is you’re observing. I’m positive those programs already exist so you wouldn’t even actually need to write it yourself.

It just seems to me like systematic random sampling is an idea whose time has gone the way of Roman numerals.

Comments

2 Responses to “Systematic random sampling: As useful as Roman numerals?”

  1. Pritam on November 12th, 2013 5:05 am

    I feel that systematic random sampling has lost its significance over the years. One of the reasons is that in systematic random sampling, the process of selecting a sample can intermingle with unknown periodic attribute within the population. For example in a sample of population if every tenth person was an Asian, and if the sampling technique intersect the periodicity of that particular attribute. Hence one can say that it the sampling technique is not random and the sample representativeness is compromised
    The other reason is that systematic random sampling is not good because everyone does not have equal probability of getting selected

  2. Pritam on November 12th, 2013 5:10 am

    I feel that systematic random sampling has lost its significance over the years. One of the reasons is that in systematic random sampling, the process of selecting a sample can intermingle with unknown periodic attribute within the population. For example in a sample of population if every tenth person was an Asian, and if the sampling technique intersect the periodicity of that particular attribute, then it will result in over representing of the Asian trait in that particular sample. Hence one can say that it the sampling technique is not random and the sample representativeness is compromised
    The other reason is that systematic random sampling is not good because everyone does not have equal probability of getting selected

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