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You get a non-random sample and any analysis based on the assumption of randomly distributed variables is no longer valid. In particular, your estimates of any variables are likely to be biased and your error estimates (standard errors or sample variances) will be incorrect. Any inferences based on statistical tests will be less reliable and may be wrong.
Sampling is a method of selecting experimental units from a population so that we can make decision about the population. Sampling design is a design, or a working plan, that specifies the population frame,sample size, sample selection, and estimation method in detail. Objective of the sampling design is to know the characteristic of the population.
The first step is to establish a sampling frame. This is a list of all teachers in the domain that you are interested in. Next you allocate a different number to each teacher. Then you use a random number generator to generate random numbers. You select each teacher whose number is generated. If the teacher has already been selected for inclusion in the sample, you ignore the duplicate and continue until you have a sample of the required size.
I don't know just taking a random guess here lets say.......12 inches
As the wikipedia article on this subject suggests, systematic sampling is most readily applied when potential sample elements are linearly ordered either in time or space. For example, one could choose to include every fifth customer arriving at a store in one's sample, which would be an instance where sample elements are ordered in time. The difficulty with many research situations in biology is obviously that sample elements are not linearly ordered. A herd of buffalo in a grassy field, for example, or a collection of microorganisms on a microscope slide. Remedies depend on circumstances. Suppose you want to apply systematic sampling in a small forest where you want to estimate the fraction of trees infested with a certain species of insect. You decide on, say, a one in five sample and that you will include 500 trees in your sampling frame in order to get a sample size of 100. To begin you walk enough parallel transects through the forest, marking sufficiently large trees as you go, to get your 500-tree sampling frame. Then you take a second trip through along transects to identify infested trees.