No. If the variable is continuous, for example, height or mass of something, or time interval, then the set of possible outcomes is infinite.
The set of all possible outcomes is the range.
A tree diagram is the way to identify and count all possible outcomes.
All possible outcomes of an experiment is known as a sample space. This will include an exhaustive list of all the possible results to be achieved.
There is 6 possible outcomes per roll of a die. So, there are 6*6*6*6 outcomes or 64 or 1296 possible outcomes.
A set of outcomes are called results. All possible outcomes are referred to as the sample space.
The sum of the probabilities of all possible outcomes is 1.
The set of all possible outcomes is the range.
Yes, it is possible to show that all deterministic finite automata (DFA) are decidable.
It is always non-negative. The sum (or integral) over all possible outcomes is 1.
Yes. The total area under any probability distribution curve is always the probability of all possible outcomes - which is 1.
Is the number of all possible outcomes of an experiment. The number depends on the experiment.
A tree diagram is the way to identify and count all possible outcomes.
All possible outcomes of an experiment is known as a sample space. This will include an exhaustive list of all the possible results to be achieved.
sample space
Not sure about only two requirements. I would say all of the following:there is a finite (or countably infinite) number of mutually exclusive outcomes possible,the probability of each outcome is a number between 0 and 1,the sum of the probabilities over all possible outcomes is 1.The Poisson distribution, for example, is countably infinite.
If the numbers (or symbols) are all different then 10 outcomes.
Yes, it is possible to demonstrate that all deterministic finite automata (DFA) are in the complexity class P.
There is 6 possible outcomes per roll of a die. So, there are 6*6*6*6 outcomes or 64 or 1296 possible outcomes.
A set of outcomes are called results. All possible outcomes are referred to as the sample space.
Find all the possible outcomes and the probabilities associated with each. That information comprises the probability distribution.Find all the possible outcomes and the probabilities associated with each. That information comprises the probability distribution.Find all the possible outcomes and the probabilities associated with each. That information comprises the probability distribution.Find all the possible outcomes and the probabilities associated with each. That information comprises the probability distribution.
you ether use a graph tree diagram or web diagram to answer the possible outcomes of the question possible outcomes meaning the number of outcomes the person will have in the probability or divide the number of favourable outcomes by the number of possible outcomes favorible outcomes meaning the number of outcomes all together
Not quite. The listing must also be exhaustive: it must contain all possible outcomes.For the roll of a fair cubic die, consider the following:Prob(1) = 1/6Prob(2) = 1/6This is a mutually exclusive listing of the outcomes of the experiment and the corresponding probabilities of occurrence but it is not a probability distribution because it does not include all possible outcomes. As a result, the total of the listed probabilities is less than 1.
A possible outcome is an element of the outcome space. All possible outcomes make up the outcome space.
sample space
I assume you mean how many possible outcomes when looking at all 13 results. It would be 2^13 = 8192