영어에서 Sample space 을 사용하는 예와 한국어로 번역
{-}
- 
                        Colloquial
                    
- 
                        Ecclesiastic
                    
- 
                        Ecclesiastic
                    
- 
                        Programming
                    
- 
                        Computer
                    
Sample Space.
In the sample space S.
Sample Spaces and Probability.
Is called the sample space.
Sample space(S): the collection of all possible outcomes.
Call the sample space S.
Well, what is the size of our sample space?
Outcomes is the sample space for the experiment.
Now, so this right over here is the sample space.
Write the sample space S.
No limitation in measuring system length and sample space.
Any subset of the sample space is an event.
Sample space refers to all possible outcomes.
So let's think about the sample space, here.
The sample space of an experiment comprises all the possible outcomes.
Every subset of this sample space is an event.
Sample Space(S)- set of all possible outcomes of a statistical experiment.
So, eight… this is possible outcomes,or the size of our sample space… possible outcomes.
The sample space is the set of all possible outcomes of the experiment.
Individually, each outcome represents a sample  point in the sample space.
Sample Space- S- set of all possible experimental outcomes.
However, this approach does not work well in cases where the sample space is uncountably infinite.
Sample Space: collection of all possible outcomes of the experiment.
The event"getting two tails and one head" consists of the following subset of the sample space.
The sample space is{HH, HT, TH, TT} where T= tails and H= heads.
Each possible result of such a study is represented by one and only one point in the sample space, which is usually denoted by S.
Defining all subsets of the sample space as events works well when there are only finitely many outcomes, but gives rise to problems when the sample space is infinite.
In the meantime, to approach this problem formally, first determine the sample space and the probability space. .
Typically, when the sample space is finite, any subset of the sample space is an event(i.e. all elements of the power set of the sample space are defined as events).
For many standard probability distributions, such as the normal distribution, the sample space is the set of real numbers or some subset of the real numbers.