Non-probability or Judgement Samples has to do with a basic researcher assumptions about the nature of the population, the researcher assumes that any sample would be representative to the population,the results of this type of samples can not be generalized to the population(cause it may not be representative as the research assumed) and the results may be biased.
Probability or Random samples is a sample that to be drawn from the population such that each element in the population has a chance to be in the selected sample the results of the random samples can be used in Statistical inference purposes
I think representative is choosing a specific group that represent, for example, your target market. Random sampling is choosing a certain number of random people
acrobat
What is the difference between 392 and 247?
the difference is also doubled
There is no difference in value between "equal" fractions: the difference is zero.
The difference between convenience and incidental sampling is that convenience sampling chooses the easiest people to reach when a sampling is done, whereas incidental sampling is done at random.
What is the difference between quota sampling and cluster sampling
tamburo
a
Simple!
sample is a noun and sampling is TO sample(verb)
Sampling error leads to random error. Sampling bias leads to systematic error.
http://www.ma.utexas.edu/users/parker/sampling/repl.htm
Statistical sampling is an objective approach using probability to make an inference about the population. The method will determine the sample size and the selection criteria of the sample. The reliability or confidence level of this type of sampling relates to the number of times per 100 the sample will represent the larger population. Non-statistical sampling relies on judgment to determine the sampling method,the sample size,and the selection items in the sample.
the difference is just that non-probability sampling does not involve random selection, but probability sampling does.
The main difference between the quota and stratified sampling is that in the stratified sampling the researcher can not select the individuals to be included in the sample (he doesn't have control over who will be in the simple), but in the quota sampling the researcher has control over who will be in the sample (he can contact certain people and include them in the sample).
There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.