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soci2030 second test.docx

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York University
SOCI 2030
Tracy Supruniuk

Sample: smaller se of cases a researcher selects to generalize to the population Census: an attempt to count everyone in a target population Non-random sampling: sampling elements are selected using something other than a mathematically random process 1) Convenience Sampling - Reliance on available subjects, choosing subjects based on availability. EX. Television interviews, people who volunteer to participate (misinterpret the population) 2) Purposive Sampling - Selects sample based on knowledge of sample & what type of sample would best serve their research goals (*can’t get a list but easily identified) – stops when the finance, or energy is reached - Similar to Sequential sampling which stops when there is no new information or diversity of cases (used in grounded theory & therefore do not know how many cases to observe – collect data until no new information emerges: theoretical saturation) Used in 3 situations: 1 – When researcher wants to use unique cases that are informative EX. Studying cultural aspects within magazines and chooses a popular magazine – trend setting 2 – Sample to select is difficult, hard to reach population EX. Hidden population – prostitutes – uses subjective information (area where prostitutes solicit, experts – and try to get as many cases) 3 – Wants to identify particular types of cases for in-depth investigation EX. Deviant case sampling: seeks cases that are different from the dominant pattern of other cases – goal is to locate unusual, different, peculiar cases that are not representative of the whole (ex. Dropouts) 3) Snowball Sampling - Researcher starts off with one case and based on information about interrelationships with that case, identifies other cases – sometimes used to sample a network (with direct or indirect links, these people are within an interconnected web of linkages and can be shown through a sociogram) 4) Quota Sampling - Try to get a non-biased sample by identifying key groups in a population (gender/class etc) and try to maintain equal number of participants from different groups, but done by still asking for participation (much like convenience sampling) only have groups and try to get equal number – predetermined number of cases in each category. Concepts related to random sampling Sampling element: unit of analysis (elements used in sampling). 4 units (individual – person, group – age/gender etc, organization – social/political, social artifacts – songs/laws which are not people but products of people) Population: Entire set of sampling elements (the entire group you are going to talk about) Study Population: Finer distinction than population EX. Want to research teachers but not all school boards allow it – research those teachers who are allowed – it genera
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