Question

Define the following terms: (a) simple random sampling, (b) systematic sampling, (c) systematic random sampling, (d) haphazard sampling, and (e) block sampling.  What are specific situations when it would be appropriate to use each and is it ever a good idea to use more than one of these?

Answer 1

a) Simple Random Sampling : A simple random sample is a subset of a statistical population in which each member of the subset has an equal probability of being chosen. A simple random sample is meant to be an unbiased representation of a group.

An example of a simple random sample would be the names of 25 employees being chosen out of a hat from a company of 250 employees. In this case, the population is all 250 employees, and the sample is random because each employee has an equal chance of being chosen.

usage : Random sampling is used in science to conduct randomized control tests or for blinded experiments.No easier method exists to extract a research sample from a larger population than simple random sampling. Selecting subjects completely at random from the larger population also yields a sample that is representative of the group being studied.

b) Systematic sampling : Systematic sampling is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point but with a fixed, periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size.

Usage : Systematic sampling involves selecting items from an ordered population using a skip or sampling interval. The use of systematic sampling is more appropriate compared to simple random sampling when a project's budget is tight and requires simplicity in execution and understanding the results of a study.

c) systematic random sampling : Systematic random sampling uses the same statistical principles as simple random sampling, that is, p values and confidence intervals are calculated the same way. However, systematic random sampling does not involve separate random selection of each household. For this reason, systematic random sampling is often used to select large samples from a long list of households.

usage : Suppose we want to create a systematic random sample of 1,000 people from a population of 10,000. Using a list of the total population, number each person from 1 to 10,000. Then, randomly choose a number, like 4, as the number to start with. This means that the person numbered "4" would be our first selection, and then every tenth person from then on would be included in our sample. Our sample, then, would be composed of persons numbered 14, 24, 34, 44, 54, and so on down the line until we reach the person numbered 9,994.

d) haphazard sampling : Haphazard sampling is a sampling method that does not follow any systematic way of selecting participants. Haphazard sampling gives little guarantee that your sample will be representative of the entire population.An example of Haphazard Sampling would be standing on a busy corner during rush hour and interviewing people who pass by.

usage : Sometimes haphazard sampling is used because it is cheaper than other sampling methods or because you aren’t able to meet random sampling requirements for technical reasons (like lack of access to computer software). Using larger sample sizes can reduce haphazard selection bias

e) block sampling : Definition and usage

Block sampling is a sampling technique used in auditing, where a sequential series of selections is made.    For example, an auditor elects to use block sampling to examine customer invoices, and intends to pick 50 invoices. She picks invoice numbers 1000 through 1049. This approach is very efficient, since a large cluster of documents can be pulled from one location. However, a more random selection method would do a better job of sampling the entire population. When using block sampling, sampling risk can be reduced by selecting a large number of blocks of samples.

We can use more than one of these samplings methods as the aim of the sampling is to estimate population parameters. The method of sampling depends on homogeneity of the population. So, if these two methods are best for these two categories then there is no problem, because the aim is the same and the sampling assumptions are fulfilled with these methods.