Topic 7: Quantitative Research - Sampling, Data Collection & Measurement

Learning Objectives
1. •Describe what sampling is and why it is necessary
2. •Understand the distinction between probability and non-probability sampling
3. •Describe the main types of sampling techniques and be able to identify them in the context of a research scenario.
4. •Distinguish between dependent and independent research variables for measurement purposes
5. •Recognise the ways that variables are measured in research, including the difference between continuous and categorical measures, and the other types of measures (i.e. binary, nominal, ordinal, interval, ratio levels, discrete and continuous)
Sampling
1. process of learning about the population based on a sample drawn from it.
2. No sample= CENSUS
  1. when information is acquired about all members of a population
  2. Don't tend to use this
    1. Bc acquiring data from the whole population would be too expensive and time-consuming.
    2. so we use predetermined and carefully planned statistical techniques to select a sample of the population from which our data will be collected.
3. Inferences (interpretations)
  1. drawn from the sample data.
    1. generalise our findings back to the whole target population.
  2. Whole pop. generalisations occur when we know it's accurate rep bc of the carefully planned sample tech
4. Sample Size
  1. must be large enough for the study to have sufficient statistical power to infer findings to the broader target population
  2. best practice for researchers to describe the sample techniques and size in publications.
  3. common limitation is that the sample size was insufficient to draw definitive conclusions in the study.
  4. have more confidence in their conclusions if they have used large samples

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Topic 7: Quantitative Research - Sampling, Data Collection & Measurement

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