Topic One: Data Collection Flashcards
Population
the whole set of items that are of interest.
Census
observes/measures every member of a population
Sample
a selection of observations taken from a subset of the population which is used to find out more of the population as a whole
Sampling Units
Individual units of a population
Sampling Frame
when sampling units of a population are individually named/numbered to form a list
Simple random sampling
every sampling unit has an equal chance of being selected
Pros and Cons of Simple random sampling
Pros:
1. Free of bias,
2. Easy and cheap to use for small populations/samples,
3. Each sampling unit has a known/equal chance of selection
Cons:
1. Not suitable when the population size or sample size is large.
2. A sampling frame is needed
Systematic sampling
the required elements are chosen at regular intervals - the start point is random
Pros and Cons for Systematic sampling
Pros:
1. Simple and quick to use
2. Suitable for large samples and large populations
Cons;
1. A sampling frame is needed
2. It can introduce bias if the order of the sampling frame isn’t random
Stratisfied sampling
where data is divided into mutually exclusive strata and a random saple is taken from each - should be proportional.
Pros and Cons of Stratisfied sampling
Pros:
1. Guarantees proportional representation
Cons:
1. Population must be divided into mutually exclusive strata
Quota Sampling
a researcher selects a sample that reflects the characteristics of the whole population
Pros and Cons of Quota Sampling
Pros:
1. No sampling frame is required
2. Easy comparison with other groups of the population
3. Quick, easy, inexpensive
4. Allows small sample to represent population
Cons:
1. Bias as it’s not random
2. Population must be divided into groups - costly
Opportunity sampling
taking a sample from people who are available at the time of study and fit a certain criteria
Pros and Cons for Opportunity Sampling
Pros:
1. Easy to carry out
2. Inexpensive
Cons:
1. Not representative
2. Bias
3. Dependent on researcher
Quantative variables/data
Variables or data associated with numerical observations
Qualitative variables/data
Variables or data associated with non-numerical observations
Continuous data
data that can take in any value within a given range e.g a measurement
Discrete data
data that can only take specific values within a given range
Classes
specific data: when data is presented in a grouped frequency table
Class boundaries
the minimum and maximum values within each class
Midpoint (within a class)
the average of the class boundary
Class width
the difference between the upper and lower class
