(Redirected from Sampling (statistics))

A Sampling Task is a selection task that requires a subset of a set.

## References

### 2017

Random sampling:
In data collection, every individual observation has equal probability to be selected into a sample. In random sampling, there should be no pattern when drawing a sample.
Significance: Significance is the percent of chance that a relationship may be found in sample data due to luck. Researchers often use the 0.05% significance level.
Probability and non-probability sampling:
Probability sampling is the sampling technique in which every individual unit of the population has greater than zero probability of getting selected into a sample.
Non-probability sampling is the sampling technique in which some elements of the population have no probability of getting selected into a sample.

### 2014

• (Wikipedia, 2017) ⇒ http://en.wikipedia.org/wiki/sampling_(statistics) Retrieved:2017-10-18.
• Within any of the types of frames identified above, a variety of sampling methods can be employed, individually or in combination. Factors commonly influencing the choice between these designs include:
Nature and quality of the frame
Availability of auxiliary information about units on the frame
Accuracy requirements, and the need to measure accuracy
Whether detailed analysis of the sample is expected
Cost/operational concerns
• The types of sampling method are:
• Simple Random Sampling
• Systematic Sampling
• Stratified Sampling
• Probability-proportional-to-size Sampling
• Cluster Sampling
• Quota Sampling
• Minimax Sampling
• Accidental Sampling
• Voluntary Sampling
• Line-Intercept Sampling
• Panel Sampling
• Snowball Sampling
• Theoretical Sampling