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The classical definition of probability is based on the feasibility at subdividing the possible outcomes of the experiments into
- a)mutually exclusive and exhaustive
- b)mutually exclusive and equally likely
- c)exhaustive and equally likely
- d)mutually exclusive,exhaustive and equally likely cases
Correct answer is option 'D'. Can you explain this answer?
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The classical definition of probability is based on the feasibility at...
Classical Definition of Probability:
The classical definition of probability is based on the feasibility of subdividing the possible outcomes of the experiments into mutually exclusive, exhaustive, and equally likely cases. This definition is based on the assumption that all outcomes are equally likely to occur.
Mutually Exclusive:
Mutually exclusive outcomes are those that cannot occur at the same time. For example, if we toss a coin, the possible outcomes are either a head or a tail. It is impossible for both a head and a tail to occur at the same time.
Exhaustive:
Exhaustive outcomes are those that cover all possible outcomes of an experiment. For example, if we toss a coin, the possible outcomes are either a head or a tail. There are no other possible outcomes.
Equally Likely:
Equally likely outcomes are those that have the same probability of occurring. For example, if we toss a fair coin, the probability of getting a head is equal to the probability of getting a tail.
Mutually Exclusive, Exhaustive, and Equally Likely Cases:
The classical definition of probability requires that the possible outcomes of an experiment be subdivided into mutually exclusive, exhaustive, and equally likely cases. This means that:
- The outcomes must be mutually exclusive, meaning that they cannot occur at the same time.
- The outcomes must be exhaustive, meaning that they cover all possible outcomes of the experiment.
- The outcomes must be equally likely, meaning that they have the same probability of occurring.
For example, if we toss a fair coin, the possible outcomes are either a head or a tail. These outcomes are mutually exclusive, exhaustive, and equally likely. The probability of getting a head or a tail is 1/2 or 50%.
The classical definition of probability is based on the feasibility of subdividing the possible outcomes of the experiments into mutually exclusive, exhaustive, and equally likely cases. This definition is based on the assumption that all outcomes are equally likely to occur.
Mutually Exclusive:
Mutually exclusive outcomes are those that cannot occur at the same time. For example, if we toss a coin, the possible outcomes are either a head or a tail. It is impossible for both a head and a tail to occur at the same time.
Exhaustive:
Exhaustive outcomes are those that cover all possible outcomes of an experiment. For example, if we toss a coin, the possible outcomes are either a head or a tail. There are no other possible outcomes.
Equally Likely:
Equally likely outcomes are those that have the same probability of occurring. For example, if we toss a fair coin, the probability of getting a head is equal to the probability of getting a tail.
Mutually Exclusive, Exhaustive, and Equally Likely Cases:
The classical definition of probability requires that the possible outcomes of an experiment be subdivided into mutually exclusive, exhaustive, and equally likely cases. This means that:
- The outcomes must be mutually exclusive, meaning that they cannot occur at the same time.
- The outcomes must be exhaustive, meaning that they cover all possible outcomes of the experiment.
- The outcomes must be equally likely, meaning that they have the same probability of occurring.
For example, if we toss a fair coin, the possible outcomes are either a head or a tail. These outcomes are mutually exclusive, exhaustive, and equally likely. The probability of getting a head or a tail is 1/2 or 50%.
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The classical definition of probability is based on the feasibility at subdividing the possible outcomes of the experiments intoa)mutually exclusive and exhaustiveb)mutually exclusive and equally likelyc)exhaustive and equally likelyd)mutually exclusive,exhaustive and equally likely casesCorrect answer is option 'D'. Can you explain this answer?
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