This one day course is designed to give participants a practical understanding of the principles of sampling. Participants will learn about the key features of random probability sampling, and the factors that need to be considered to obtain efficient, unbiased samples.
Course outline
Course content covers:
- an introduction to the different sampling approaches with particular reference to random probability methods
- over-sampling different sub-groups
- selecting multi-phase clustered samples
- selecting stratified samples
- the impact of variable sampling fractions, clustering and stratification on sample efficiency.
The course will enable participants to design and select random probability samples, considering the quality and statistical efficiency of the samples obtained.
Who is it aimed at?
You will find the course useful if:
- you are a quantitative researcher or statistician planning to be involved in sampling
- you need to make informed judgments about proposed sampling approaches
- you use social survey findings and want to be able to assess the quality of the samples obtained
- you commission or manage quantitative research in central or local government, health or other sectors.
Learning outcomes
By the end of the course, participants will be able to:
- discuss the key features of random probability sampling and its advantages over other methods
- design an efficient sampling strategy.
- measure the impact of different sampling design features, including variable selection probabilities, clustering and stratification, on standard errors and confidence intervals
- select an efficient multi-stage sample.
Cost and booking
The full price of this course is £350.
We offer discounts to students, academics and those working in the voluntary sector.
Participants will be limited to a maximum group size of 10.