Sampling Flashcards
1
Q
What is a Sampling Frame?
A
- A list from which a sample is drawn.
- Derived from population elements
- Customer databases, member lists, phone books
- No perfect sampling frame exists
2
Q
Sampling Procedures
A
- Process of drawing the right sample
- Divided into non-probability and probability procedures
3
Q
Non-Probability Sampling
A
- Convenience
- Judgement
- snowball
- Quota
4
Q
Convenience Sampling (NP)
A
- being included in a sample is purely a matter of convenience
- easy to access
- not the most suitable can create sampling error
- Poor reflection of target population
- Used in exploratory research for insights to a research problem
5
Q
Judgement Sampling (NP)
A
- Hand picked by researcher
- Possess certain characteristics
- May be suitable procedure or invalidate results
6
Q
Snowball Sampling (NP)
A
- Respondents to identify and select other respondent
- relies on ability to locate initial set of respondents
- Useful for niche or hard to reach populations
- May lead to bais due to similarity
7
Q
Quota Sampling (NP)
A
- Goal is to build a sample that looks like the larger population
- Ensures various sub groups of population are represented in a specific proportion
- Digital and online ease
- Relies on in-depth sampling frame
8
Q
Probability Sampling
A
- Random sampling
- Systematic sampling
- Stratified sampling
- Cluster Sampling
9
Q
Random Sampling (P)
A
- Each respondent has a known equal chance of being selected
- Ensures sampling error is not added by researchers
10
Q
Systematic Sampling (P)
A
- Randomly selected first respondent, then develop a system for subsequently sampling
- Once the first is selected, all population elements no longer have an equal chance
11
Q
Stratafied Sampling (P)
A
- Breaks populations down into mutually exclusive strata (subgroups), then sampled within these strata.
- Strata must share similar population parameters or characteristics (homogenous)
12
Q
Cluster Sampling (P)
A
- Splitting a population into sub-groups (clusters)
- Clusters should be heterogenous (different)
- sample all population elements of a few clusters
- Maintains randomness and efficiency.
13
Q
Segmentation Bases
A
- Break down heterogenous populations into homogenous ones
- Usage
- Demographics
- Psychographics
- Benefits
- Geographic
14
Q
Usage Segmentation
A
- Considers the usage frequencies of consumers
- Usage patterns or commitment levels
- Eg. Non-users, loyalist, switchers, emergents
- Importance of attracting first time users.
15
Q
Demographics segmentation
A
- Basic descriptors used to describe an individual
- Age, gender, income, occupation, education
- Used to profile or compare
