1 Data collection Flashcards
Large Data set
A huge spreadsheet of data covering weather records in 1987 and 2015
Population
The whole set of items that are of interest
Quota sampling
A non random method of sampling where the sample reflects the characteristics of the population
Quantitative data
Data which is numerical e.g. height
Discrete data
Data that can only take certain values e.g. ( number of students in a class, there can’t be half a student)
Sampling frame
A list of sampling units
Sample
A selection of observations taken from a population
Continuous
Data that can take any value in a given range e.g. time in a race
Qualitative
Data which is not numerical but fits into categories e.g. eye colour
Random
When every item in the population has an equal chance of being chosen for the sample
Systematic
A random method of sampling where items are chosen at regular intervals from an ordered list
Stratified
random sampling where the population is divided into strata (eg males and females) and then randomly picked from them
Census
Used to observe every member of the population
Opportunity
Non random method which consists of taking a sample from the items available to you at a certain time
Sampling unit
Individual units of a population
Census pros and cons
+ should give a completely accurate result
- time consuming
- expensive
- large quantities of data
Sample pros and cons
+quick
+cheap
- may not be that accurate
- sample may not be large enough to give information about subgroups
Simple random sampling pros and cons
+free of bias
+easy and cheap for small sample
+each sampling unit has a known and equal chance of selection
- not suitable for large numbers
- a sample frame is needed
Stratified sampling pros and cons
+sample accurately reflects the population structure
+guarantees proportional representation of groups within a population
- population must be split into distinct strata
- selection within each stratum suffers from same cons as random sampling
Systematic sampling pros and cons
+simple and quick to use
+suitable for large samples and large populations
- a sampling frame is needed
- it can introduce bias if the sampling frame is not random
Quota sampling pros and cons
+allows a small sample to still be representative of the population
+no sampling frame required
+quick, easy and inexpensive
+allows for easy comparison between different groups within a population
- could be biased
- population must be divided into groups, which can be costly and inaccurate
- increasing scope adds time and expense
- non responses are not recorded
Opportunity sampling pros and cons
+easy to carry out
+cheap
- unlikely to provide a representative sample
- highly dependent on the individual researcher
