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SOCI 2003B: Sociological Methods Colleen Anne Dell, Ph.D. Carleton University, Department of Sociology & Anthropology Canadian Centre on Substance Abuse.

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Presentation on theme: "SOCI 2003B: Sociological Methods Colleen Anne Dell, Ph.D. Carleton University, Department of Sociology & Anthropology Canadian Centre on Substance Abuse."— Presentation transcript:

1 SOCI 2003B: Sociological Methods Colleen Anne Dell, Ph.D. Carleton University, Department of Sociology & Anthropology Canadian Centre on Substance Abuse October 26, 2006 Data Collection & the Logic of Sampling FUNDAMENTAL TECHNIQUES - QUALITATIVE DATA GATHERING & ANALYSIS

2 OUTLINE 1. Data Collection: 3 Methods 2. Why sample? 3. Non-probability sampling 4. Probability sampling a. Theory and Logic b. Techniques c. Design

3 WORKSHOP Research team problem solving – Groups 8 - 15

4 How can social scientists select a few people for discussion and make discoveries that apply to hundreds of millions they don’t observe? The logic of sampling provides the answer (Babbie and Benaquisto 2002:161).

5 HYPOTHETICAL NEW CARLETON UNIVERSITY POLICY Left handed people cheat on exams and therefore are expelled from the Carleton University campus as of November 1, 2002. 1. How can you study this? (sample) 2. What sources can you use to collect data?

6 1. DATA COLLECTION: 3 METHODS 1. Ask people 2. Observe behaviour OBSERVE BEHAVIOUR: Obtaining measurements by observing behaviour, traces of behaviour, or physical objects without interacting with research subjects. 3. Examine existing data

7 2. WHY SAMPLE? SAMPLING… “…the process of selecting observations” (Babbie & Benaquisto 2002:162). “…is a process of systematically selecting cases for inclusion in a research project” (Neuman 1991:198).

8 3. NON-PROBABILITY SAMPLING When people or objects being considered for selection in a sample DO NOT HAVE a known probability (or chance) of being selected. 1. Convenience sampling 2. Purposive theoretical sampling 3. Quota sampling 4. Snowball sampling

9 4. PROBABILITY SAMPLING When ALL CASES in the population have A KNOWN PROBABILITY (or chance) of being included in the sample.

10 (A) THEORY AND LOGIC “To provide useful descriptions of the total population, a sample of individuals from a population must contain essentially the same variations that exist in the population”.

11 Based on 2 criteria: (1) The sample provides a faithful representation of the population from which it was selected. (2) The sample is reliable with respect to the probability that the sample is indeed representative of the true population. BIAS: “Those selected are not typical or representative of the larger populations they have been chosen from”.

12 (B) TECHNIQUES

13 (C) DESIGN 1. Overall random sampling 2. Simple random sampling 3. Systematic sampling 4. Stratified sampling a. Proportionate stratified sampling b. Disproportionate stratified sampling 5. Cluster sampling

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