Topic 7: Quantitative
Research - Sampling, Data
Collection & Measurement
1 Learning Objectives
1.1 •Describe what sampling is and why it is necessary
1.2 •Understand the distinction between probability and non-probability sampling
1.3 •Describe the main types of sampling techniques and be able to
identify them in the context of a research scenario.
1.4 •Distinguish between dependent and independent research
variables for measurement purposes
1.5 •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)
2.1 process of learning about the population
based on a sample drawn from it.
2.2 No sample= CENSUS
2.2.1 when information is acquired about
all members of a population
2.2.2 Don't tend to use this
184.108.40.206 Bc acquiring data from the whole population would be
too expensive and time-consuming.
220.127.116.11 so we use predetermined and
carefully planned statistical
techniques to select a sample of the
population from which our data will
2.3 Inferences (interpretations)
2.3.1 drawn from the sample data.
18.104.22.168 generalise our findings back to the whole target population.
2.3.2 Whole pop. generalisations occur when
we know it's accurate rep bc of the
carefully planned sample tech
2.4 Sample Size
2.4.1 must be large enough for the study to have
sufficient statistical power to infer findings to the
broader target population
2.4.2 best practice for researchers to
describe the sample techniques
and size in publications.
2.4.3 common limitation is that the
sample size was insufficient to
draw definitive conclusions in
2.4.4 have more confidence in
their conclusions if they have
used large samples