1. Types of method Quantitative: – Questionnaires – Experimental designs Qualitative: – Interviews – Focus groups – Observation Triangulation

2. What is sampling? (Babbie) Polls and other forms of social research, rest on observations. The task of researchers is to select the key aspects to observe, or sampling. Generalizing from a sample to a larger population is called probability sampling and involves random selection.

3. Advantages of Sampling Less costs – cheaper than studying whole population Less errors due to less fatigue – better results Less time – quicker Destruction of elements avoided – eg bulbs

4. Concepts in sampling Population (or target population) – entire group of people, events or things of interest that the researcher wishes to investigate Element – a single member of the population Sampling Frame – a listing of all the elements in the population from which the sample is drawn Sample – a subset of the population Subject – a single member of the sample

6. Sampling decisions 1.What is the relevant target population of focus to the study? 2.What exactly are the parameters that we are interested in studying? 3.What kind of sampling frame is available? 4.Should a probability or non-probability method be chosen? 5.What is the sample size needed? 6.What costs are attached to the sampling? 7.How much time can be spent collecting the data?

7. Probability & Non-probability Sampling Probability Sampling – Used when researchers want precise, statistical descriptions of large populations. – In order to provide useful descriptions of the total population, a sample of individuals from a population must contain the same variations that exist in the population. – the elements in the population have some known chance or probability of being selected as sample subjects Non-probability Sampling – the elements do not have a known or predetermined chance of being selected as subjects – Difficult to generalise to the population Decision tree - SLT ch.11

9. Types of Probability Sampling Simple random sampling – every element in the population has a known and equal chance of being selected as a subject – Not the most accurate method Complex (or restricted) probability sampling – procedures to ensure practical viable alternatives to simple random sampling, at lower costs, and greater statistical efficiency

10. Simple Random Sampling Is the most representative of the population for most purposes Disadvantages are: – Most cumbersome and tedious – The entire listing of elements in population frequently unavailable – Very expensive – Not the most efficient design

11. Complex Probability Sampling Systematic sampling Stratified random sampling Cluster sampling Area sampling

13. Multi-stage sampling

14. Non-probability Sampling Convenience sampling – Survey whoever is easily available – Used for quick diagnosis of situations Simplest and cheapest Least reliable Purposive sampling – Judgement sampling: Aim is to achieve “saturation” of cases – Snowball sampling – Quota sampling

15. Qualitative sample designs Not necessarily representative of population Use non-probability methods Key issue: avoiding systematic bias Avoid ‘paralysis by analysis’