Important statistical terms Population: a set which includes all measurements of interest to the researcher (The collection of all responses, measurements,

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Presentation transcript:

Important statistical terms Population: a set which includes all measurements of interest to the researcher (The collection of all responses, measurements, or counts that are of interest) Sample: A subset of the population

Why sampling? Get information about large populations   Less costs   Less field time  Can Do A Better Job of Data Collection  More accuracy i.e. Can Do A Better Job of Data Collection   When it’s impossible to study the whole population

Types of sampling Non-probability samples Probability samples

Non probability samples Person in the street Sample is selected from elements of a population that are easily accessible. Self selection – Rely on the individuals to respond to a questionnaire usually via /letter. Quota sample – Try to get a specific number of minority groups in your sample. Quota sample – Try to get a specific number of minority groups in your sample.

Non probability samples Probability of being chosen is unknown Cheaper- but unable to generalise Large potential for bias

Probability samples Random sampling Each subject has a known probability of being selected Allows application of statistical sampling theory to results to: Generalise Test hypotheses

Conclusions Probability samples are the best Ensure Representativeness Precision

Methods used in probability samples  Simple random sampling  Systematic sampling  Stratified sampling  Cluster sampling

Simple random sampling

Table of random numbers

Always picking a person at random based on the position of their name on a list. E.g. Pick every 6 th person in the phone book. Systematic sampling

Cluster sampling Cluster: a group of sampling units close to each other i.e. crowding together in the same area or neighborhood

Cluster sampling Section 4 Section 5 Section 3 Section 2Section 1

Stratified sampling Stratified sampling Some research is done to identify characteristics in the population. Researchers then randomly sample sufficient people from each category in proportion to the population.

 Sources of bias Inaccurate response (information error) Exclude one or more groups from the sample. (Coverage error) Include a group that isn’t part of your population. (Coverage error)  Sampling error (random error) Errors in sample

Precision Cost

Task Work in pairs to answer the questions on Pages 8 and 9. Refer to page 7 for details on the sampling methods. The chat should mainly be about the work. Finish up to Q14 or take it away for homework.