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Sampling Techniques

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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.

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**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.

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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.

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**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).

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**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.

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**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.

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**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.

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**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.

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**Random Sampling Methods - Continued**

Destructive Sampling → applicable to products only; → products chosen randomly, tested for quality control.

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**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!

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**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

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**Multi-staged Random Sample**

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

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**Systematic Random Sample**

c) Every fiftieth family in the Unionville telephone book is surveyed by phone. Systematic Random Sample

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**d) Jonathon randomly selects three cards from a standard deck of cards.**

Simple Random Sample

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2. In a town of 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?

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