TYPES OF SAMPLING DESIGNS
    Simple Random Sampling
    Systematic Sampling
    Stratified Sampling
    Implicit Stratification in Systematic Sampling
    Illustration: Sampling University Students

    Simple random sampling, as the name suggests, is the most basic form of probability sampling.  Members of the population are assigned numbers, and a set of random numbers is generated to identify the members of the population who will be in the sample.

    Depending on the form of the sampling frame, a systematic sample may be easier: selecting every kth (e.g., 10th, 1547th, etc.) name on the list.  Unless there is some cyclical pattern in the list, this is essentially the equivalent of a simple random sample.

    Probably sampling produces relatively representative samples, but this can be improved by stratifying the sampling frame.  A simple random sample of college students would be approximately the right numbers of Freshman, Sophomores, Juniors, and Seniors. By identifying students' class-standings in advance, we can sample separately from each class and get precisely the right number from each.

    Often, sampling frames are structured so as to group similar people together (listing students by class, for example).  In such cases, a systematic sample will automatically enjoy a degree of stratification, as you'll see in the chapter.