Lesson 3 Flashcards
Quantitative Sampling
- Goal: to generalize the population
- Uses large, random samples
Qualitative Sampling
- Goal: to generate a deeper understanding
- Uses smaller, purposeful samples
- Data saturation
Data Saturation
= the point in the research process when no new information is discovered in data analysis
Probability Sampling
- Involved selecting random samples of subjects from a given population
- Each member of the population has an equal chance to be selected to be part of the sample
Probability Sampling Methods (4)
- Random Sampling
- Stratified Sampling
- Cluster Sampling
- Stage Sampling
Random Sampling
- Completely random sample of the population
- Used when believed that the population is relatively homogeneous
Systematic Sampling
- Every Kth element of a sampling frame is chosen for the sample
- K is the sampling interval, with the first element being chosen
Stratified Sampling
- Modification of simple random sampling and systematic sampling
- Taking a random sample from various strata
Strata
= smaller sub-group
Cluster Sampling
- Population is separated into clusters to create a sample
- Common is many large-scale surveys
Non-probability Sampling (4)
= a sampling technique in which the researcher selects samples based on the subjective judgement of the researcher rather than random selection
- Quota Sampling
- Purpose Sampling
- Snowball Sampling
- Convenience Sampling
Quota Sampling
= in which various strata are identified by the researcher who ensures that these strata are proportionately represented within the sample to improve its representatives
Purpose Sampling
= strategy in which participants are selected on the basis that they are considered to be typical of a wider population
Snowball Sampling
= strategy through which the first group of participants is used to nominate the next cohort of participants
Convenience Sampling
= strategy that used the most conveniently accessible people to participate in the study