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Tuesday October 8th 2013 Poli 2P80.docx

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Political Science
Brad Walchuk

Tuesday October 8 2013 Poli 2P80: Sampling Slide 1: The logic behind sampling - researchers are faced with a problem: the populations we wish to study are almost always so large that we are unable to gather information from every case - solution: the researcher chooses a sample – a carefully chosen subset of the population – and use information gathered from the cases in the sample to generalize to the population Slide 2: Why sample? - we should collect a sample that is representative to the population you are studying - representative: the sample has the same characteristic as the population - example: o instead of surveying every Brock University student, a researcher will select a small number of Brock students o selecting only female CHYS majors may be a problem, it is not representative of all Brock students Slide 3: Why representative? - a recognition that people with different characteristics have different views, and that these views are reflected in results o which views do we include? - It is important to be inclusive and reflect the community we wish to study - An unrepresentative sample can (and likely will) lead to a biased or inaccurate result o Furthermore, it is not accurate (it misses the target) Slide 4: Two types of sampling - non-probability sampling o non-probability in this case means non-random o a researcher usually has a set population they wish to study and a set number of cases to include - probability sampling o probability sampling almost always strives for and element of randomness o randomness is achieved by calculating the population size and sample ratio Slide 5: Types of non-probability sampling - haphazard (convenience) - quota - purposive (judgmental) - snowball - deviant - sequential Slide 6: Haphazard Sampling - the researcher selects anyone he or she happens to come across o example:  interviews on the street in front of City TV, radio shows that ask viewers to call in and give an opinion o purpose: mostly for entertainment purposes, but also be based on need (unlikely for ‘real; social researchers) Slide 7: Quota Sampling - the researcher selects general categories to analyze and then selects a pre- determined number of cases from each (using a probability or non- probability method) - example: o studying 50 people from the following age categories 10-19, 20-29, 30-39 - purpose: set a goal to make a project more manageable, ensure some level of representativeness Slide 8: Snowballing sampling - researcher begins with one case and then, based on information provided, is able to seek out additional cases (repeated until enough cases) - example: o asking a friend to answer a survey and asking that friend if they know anyone else who would answer a survey and asking the friend of a friend ect. - Purpose: time efficient ways of collecting data, likely of finding similar people (if targeting a specific group) Slide 9: Purposive or Judgmental sampling - the researchers used a variety of methods to locate as many specific cases as possible, generally from hard-to-reach group - example: o re
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