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Sampling Techniques. Samples. Having clearly identified a thesis statement or question, as well as the population, variables and type of data involved, a researcher can begin to conduct his or her study;
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Samples • Having clearly identified a thesis statement or question, as well as the population, variables and type of data involved, a researcher can begin to conduct his or her study; • To conduct research, data from a sample must be collected, which could involve medical testing, laboratory analyses, surveys, etc.
Samples - Continued • The sample must be: 1. representative of the population; 2. appropriately sized (the larger the better); 3. unbiased; 4. random (selections occur by chance); • The above criteria are interrelated.
Samples - Continued • To ensure that the four criteria are met, careful planning is needed (any errors in the sample will result in unreliable conclusions); • One of several methods can be chosen to achieve randomness when selecting a sample.
Random Sampling Methods Six methods are commonly employed. 1. Simple Random Sampling → all individuals in the population have an equal likelihood of being chosen; → for example, number all students and select the numbers from a hat (minimize the level of control that the researcher has).
Random Sampling Methods - Continued 2. Systematic Random Sampling → used when you are sampling a fixed percentage of the population; → randomly select a starting point, then select every nth individual; → n is referred to as the sampling interval (n = pop size/sample size); → for example, number all students in a list, randomly select a starting point in the list, and select every nth individual.
Random Sampling Methods - Continued • Stratified Random Sampling → population is divided into strata, or groups; → randomly select members of each stratum (the number selected is proportional to the stratum’s size); → for example, divide our population into 9’s, 10’s, 11’s and 12’s, and randomly select members in each grade.
Random Sampling Methods - Continued • Cluster Random Sampling → population is organized into groups; → groups are randomly selected, and all members of the group are sampled; → for example, divide our school into homerooms, randomly select homerooms, and sample all students in selected homerooms.
Random Sampling Methods - Continued • Multi-Stage Random Sampling → population is organized into groups; → randomly select groups, and then randomly select members in these groups (an equal number selected per group); → for example, repeat the steps for Cluster Random Sampling, but then randomly select students in each selected homeroom.
Random Sampling Methods - Continued • Destructive Sampling → applicable to products only; → products chosen randomly, tested for quality control.
Random Sampling Methods - Continued • The sampling method chosen depends on the population of interest; • Sometimes, methods can be combined; • Careful planning is the key to generating reliable results – always have contingency plans!
1. Determine the type of sampling method used in each scenario. a) The Ontario government randomly selects five high schools in Ontario and surveys each teacher in those schools. Cluster random sampling
b) You wish to survey 100 employees at Trillium Shopping Plaza (contains 216 stores). You randomly select 10 stores, then randomly select 10 employees from each store. Multi-staged Random Sample
c) Every fiftieth family in the Unionville telephone book is surveyed by phone. Systematic Random Sample
d) Jonathon randomly selects three cards from a standard deck of cards. Simple Random Sample
2. In a town of 120 000 people, smoking has been banned in all restaurants. A committee of students wants to find out what the whole town thinks of this new law. The committee wants to survey 1460 people. Which sampling technique is most appropriate?
