A probability sample is one in which each member of the population has the same probability of being included. An alternative and equivalent definition is that it is a sample such that the probability of selecting that particular sample is the same for all samples of that size which could be drawn from the population.
Not sure about the "best" definition. It is the set of all possible outcomes for the event.
Set of all possible outcomes.
Since there is only one definition given, it has to be better than the ones which are not even featured!
In a probability sample, each unit has the same probability of being included in the sample. Equivalently, given a sample size, each sample of that size from the population has the same probability of being selected. This is not true for non-probability sampling.
There are two equivalent ways of defining a simple random sample from a larger population. One definition is that every member of the population has the same probability of being included in the sample. The second is that, if you generate all possible samples of the given size from the population, then each such sample has the same probability of being selected for use.
There are two equivalent definition. Definition 1: A simple random sample is one for which each element has the same probability of being included in the sample. Definition 2: A simple random sample is one where all sample of that size have the same probability of being selected. Although the words are similar, the first refers to the selection of individuals from the population whereas the second refers to the samples.
It is the set of all possible outcomes.
Not sure about the "best" definition. It is the set of all possible outcomes for the event.
Set of all possible outcomes.
It is the space consisting of all possible outcomes of the experiment.
Since there is only one definition given, it has to be better than the ones which are not even featured!
In a probability sample, each unit has the same probability of being included in the sample. Equivalently, given a sample size, each sample of that size from the population has the same probability of being selected. This is not true for non-probability sampling.
There are two equivalent ways of defining a simple random sample from a larger population. One definition is that every member of the population has the same probability of being included in the sample. The second is that, if you generate all possible samples of the given size from the population, then each such sample has the same probability of being selected for use.
In the context of a sample of size n out of a population of N, any sample of size n has the same probability of being selected. This is equivalent to the statement that any member of the population has the same probability of being included in the sample.
The key feature is that each sample of the given size has the same probability of being selected as the sample. Equivalently, each unit in the population has the same probability of being included in the sample.
Since probability is not a geometric concept, there is no definition for it in geometry.
Probability.