WJEC Maths for AS: Applied sample

1 Statistical sampling 12 Systematic sampling is most suited when the items being studied can be sorted into a sequence and where the allocation of a random number to each item would be difϐicult. • Opportunity sampling – involves taking people from the population that are available at the time and are willing to take part in a survey. For example, you could ask people coming out of a station their opinion on the service offered by the train companies. This is a fast way of completing a survey but it can produce a biased sample, which means it does not fairly represent the population. 1.4 Selecting or critiquing sampling techniques The ideal sample will: • Be large enough • Represent the population • Be unbiased. It is important to be able to look at a sampling technique critically to see if the sample is biased in any way. Here are some things to consider: The sample size – too small a sample may produce strange results, e.g. the sample could produce all people of a certain sex, age, income, etc. The time of day the sample is taken – if you took a sample of train passengers at 8am you bias the sample towards people who were working. Where the sample is taken – if you wanted information about the types of holidays people took, taking it at an airport would bias it towards those people taking their holidays abroad. Advantages and disadvantages of different sampling techniques Simple random sampling Advantages • Least biased of all sampling techniques – each member of the total population has an equal chance of being selected. • Easily performed (e.g. picking numbers out of a hat, using a website, using the random number on a calculator or a random number function in a spreadsheet). • Sample is highly representative of the population. Disadvantages • Time consuming and tedious to perform. • Can lead to poor representation of the overall population, if certain members are not hit by the random numbers generated.