Geographical methods Flashcards
What are the 7 sampling methods?
- Simple random sampling
- stratified random sampling
- systematic sampling
- cluster sampling
- Quota sampling
- convenience sampling
- snowball sampling
what are under probability sampling methods?
- Simple random sampling
- stratified random sampling
- systematic sampling
- cluster sampling
what are under non-probability sampling
- Quota sampling
- convenience sampling
- snowball sampling
What is the appropriate use and how to conduct of random sampling?
Appropriate use:
— When the whole population is available for a survey
— When every member has an equal chance of being selected
— When the area is large or time-limited
How to conduct:
— Use random tools like number generators or tables
— Select people based on generated numbers (e.g., 2nd, 5th person)
What is simple random sampling
Definition:
Simple random sampling is a method where each population member has an equal chance of being selected.
What is the appropriate use and how to conduct of systematic sampling?
Appropriate use:
— When sufficient representation of people is available
— When there’s a continuous stream of people (e.g., on the street)
How to conduct:
— Select individuals from a larger population starting at a random point, then choose with a fixed interval (e.g., every 1 male followed by 1 female)
What is systematic sampling
Definition:
Systematic sampling selects every nth item from a population based on a calculated interval.
What is the appropriate use and how to conduct of stratified sampling?
Appropriate use:
— When investigating specific subgroups
— When proportional representation of mixed characteristics is needed
How to conduct:
— Divide the population into relevant subgroups based on relevant characteristics (eg. gender, race)
— Calculate the sample size for each subgroup
— Select samples using random or systematic methods
What is stratified sampling
Definition:
Stratified sampling is a probability sampling method where the population is divided into distinct subgroups, and samples are drawn from each subgroup.
Pros and cons of systematic sampling!
Pros:
— Efficient and easy to implement
— Provides even population coverage
Cons:
— Can introduce bias if patterns align with the interval
— Limited randomness after the first selection
What is cluster sampling?
Cluster sampling refers to grouping a large population of people up into smaller groups. Random clusters are then selected to form a sample
Example:
Imagine a school with 20 classrooms. To do a survey, you randomly select 5 classrooms (clusters) and then survey all students in those selected classrooms, rather than surveying students from every classroom.
pros and cons of stratified sampling
Pros:
— Ensures proportional representation from each subgroup
— Reduces bias by sampling from all strata
Cons:
— Requires clear subgroup definitions, which can be challenging
— Can be time-consuming to collect and analyze data from multiple subgroups
Pros and cons of simple random sampling!
Pros:
— Unbiased results due to equal selection chance
— Simple and quick to implement
Cons:
— Can be costly for large populations
— May not represent specific subgroups efficiently
Pros and cons of cluster sampling!
Pros:
— Convenient and time-saving as it involves fewer groups
— Less hassle and complexity in organization
Cons:
— Might miss some minorities if they are not in chosen clusters
— Less accurate if clusters vary widely in characteristics
What is quota sampling?
A non-random selection technique where a researcher chooses a sample group to represent particular population characteristics
EG:
if you wanna sell a meal kit, you identify the different groups in the population - muslims, vegens, meat eaters. Then you take 200 people from each group and conduct research.
pros and cons for quota sampling?
Advantages:
— Provides clear distinction and diversity of responses
— Ensures involvement of various stakeholders
Disadvantages:
— Requires extra work for the researcher
— Generalizes individuals based on their community rather than personal experiences
Convenience Sampling! WHAT IS IT??
Convenience sampling is a non-probability method where samples are selected based on their easy accessibility to the researcher.
It’s like picking the candies on top of the jar because they’re easiest to reach, potentially missing those below.
pros and cons of convenience sampling!!
Pros:
— Practical and cost-effective
— Easy to implement
Cons:
— May introduce bias
— Less representative of the entire population
What is snowball sampling?
Snowball sampling is a nonprobability method where existing participants recruit new ones from their acquaintances, causing the sample to grow like a rolling snowball.
Pros and cons of snowball sampling
Advantages:
— Accesses hard-to-reach populations
— Builds trust and rapport
Disadvantages:
— Potential for biased samples
— Lacks statistical rigor
