Week Three Flashcards
What is a sampling frame and a sampling unit?
Sampling frame: the list from which the elements of the population are selected
Sampling unit: any single unit sampled from the population, primary sampling units - entitles selected in the first stage of the sample, secondary sample units - entities selected in the second stage of the sample if there is one
What are the two types of generalisability
Sample generalisability: ability to generalise from a subset of a larger population (I.e. Sample) to that population itself. This often occurs through inferential statistics
Cross- population generalisability (external validity): ability to generalise from the findings about one group, population, or setting to other groups, populations or settings
What is a sampling error
Any difference between the characteristics of a sample and the characteristics of the population from which it was drawn
The larger the sampling error, the less representative the sample is of the population
What is probability
Sample methods that allow us to know in advance how likely it is that any element of a population will be selected
Random selection: everyone in the population has a know / equal chance to be picked
Non-probability: sample methods in which the likelihood of selection is not know in advance
What does probability sampling do
Allows researchers to select study subjects to be statistically representative of population they want to learn about (generalisability)
What is simple random sampling?
Identifies cases strictly on the basis of chance eg random number tables
Typically every subject has equal probability of being selected
CANNOT do this without a sampling frame that contains every element of the population
Can be done with or without replacement sampling
What is replacement sampling
Each element is returned to the sampling frame from which it is selected so that it may be sampled again
What is systematic random sampling?
The first element is selected randomly from a list, and then every nth element thereafter is selected
What are the three steps of systematic random sampling?
Calculate sampling interval: the total number of cases in pop is divided by the number of cases required in the sample
Identify the first case to be selected: a number within the sampling interval is randomly selected and used to select the first case
Selection of subsequent cases: every nth case is selected, wherein is the sampling interval
What is stratified random sampling
Uses information known about key characteristics of the population prior to sampling to make the process more efficient
Often used to ensure that subjects who have a Rare or uncommon characteristics are adequately represented in the sample
What are the two steps of stratified random sampling?
- Distinguish all elements in the populations (I.e. In the sampling frame) according to their value on some relevant characteristic.
- that characteristic forms the sampling strata
- each element must belong to one and only one stratum - Sample elements randomly from within each strata
What is proportionate and disproportionate stratified sampling
Proportionate ratified sampling: every group is equally proportional to its size in the population
Disproportionate stratified sampling: proportionate of each group is unite nationally varied from population - useful to include small or underrepresented groups
What is multistage cluster sampling
Sampling in which elements are selected in two or more stages
- Clusters: preexisting groups of elements in a population - a random sample of clusters is selected
- Within clusters: within each cluster a random sample of elements is selected
What is non probability sampling
Each member of population is an unknown probability of being selected
What are the four types of non probability sampling
Availability or convenience
Snowball
Quota
Purposive/judgment
What is convenience sampling
Elements are selected because they are available or easy to find
What is quota sampling
Elements are selected to ensure that the sample represents certain characteristics of the population
Similar to stratified probability sampling but generally less rigorous and precise in selection procedures
What is purposive sampling
Each sample element is selected for a purpose. Usually because if the unique position of the sample elements
May involve studying the entire population of some limited group or a subset of a population