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According to the statistical definition of probability, the probability of an event A is the
- a)limiting value of the ratio of the no. of times the event A occurs to the number of times the experiment is repeated
- b)the ratio of the frequency of the occurrences of A to the total frequency
- c)the ratio of the frequency of the occurrences of A to the non-occurrence of A
- d)the ratio of the favourable elementary events to A to the total number of elementary events
Correct answer is option 'A'. Can you explain this answer?
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According to the statistical definition of probability, the probabilit...
The Definition of Probability
Probability is a measure of the likelihood or chance of an event occurring. The statistical definition of probability is based on the concept of frequency. It states that the probability of an event A is the limiting value of the ratio of the number of times the event A occurs to the number of times the experiment is repeated, as the number of repetitions approaches infinity.
Breaking Down the Definition
To understand the statistical definition of probability, we can break it down into its components:
- Event A: This refers to the specific outcome or set of outcomes that we are interested in. For example, if we are rolling a die, event A could be rolling a 6.
- Experiment: This refers to the process or procedure that we use to generate outcomes. For example, if we are rolling a die, the experiment would be rolling the die.
- Ratio of the number of times the event A occurs to the number of times the experiment is repeated: This is the fraction that represents the proportion of times that event A occurs over the total number of times that the experiment is repeated.
- Limiting value: This refers to the value that the ratio approaches as the number of repetitions of the experiment approaches infinity.
Putting it all together, the statistical definition of probability states that the probability of an event A is the fraction of times that event A occurs over the total number of times the experiment is repeated, as the number of repetitions approaches infinity.
Why is this Definition Important?
The statistical definition of probability is important because it provides a precise and objective way of measuring the likelihood of events. By counting the number of times that an event occurs and comparing it to the total number of repetitions of the experiment, we can calculate a probability that reflects the true frequency of the event. This definition also allows us to use probability to make predictions about future events based on past data, which has many practical applications in fields such as finance, engineering, and medicine.
Probability is a measure of the likelihood or chance of an event occurring. The statistical definition of probability is based on the concept of frequency. It states that the probability of an event A is the limiting value of the ratio of the number of times the event A occurs to the number of times the experiment is repeated, as the number of repetitions approaches infinity.
Breaking Down the Definition
To understand the statistical definition of probability, we can break it down into its components:
- Event A: This refers to the specific outcome or set of outcomes that we are interested in. For example, if we are rolling a die, event A could be rolling a 6.
- Experiment: This refers to the process or procedure that we use to generate outcomes. For example, if we are rolling a die, the experiment would be rolling the die.
- Ratio of the number of times the event A occurs to the number of times the experiment is repeated: This is the fraction that represents the proportion of times that event A occurs over the total number of times that the experiment is repeated.
- Limiting value: This refers to the value that the ratio approaches as the number of repetitions of the experiment approaches infinity.
Putting it all together, the statistical definition of probability states that the probability of an event A is the fraction of times that event A occurs over the total number of times the experiment is repeated, as the number of repetitions approaches infinity.
Why is this Definition Important?
The statistical definition of probability is important because it provides a precise and objective way of measuring the likelihood of events. By counting the number of times that an event occurs and comparing it to the total number of repetitions of the experiment, we can calculate a probability that reflects the true frequency of the event. This definition also allows us to use probability to make predictions about future events based on past data, which has many practical applications in fields such as finance, engineering, and medicine.
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According to the statistical definition of probability, the probabilit...
The probability of an event is the proportion (relative frequency) of times that the event is expected to occur when an experiment is repeated a large number of times under identical conditions. We will represent outcomes and events by capital letters
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According to the statistical definition of probability, the probability of an event A is thea)limiting value of the ratio of the no. of times the event A occurs to the number of times the experiment is repeatedb)the ratio of the frequency of the occurrences of A to the total frequencyc)the ratio of the frequency of the occurrences of A to the non-occurrence of Ad)the ratio of the favourable elementary events to A to the total number of elementary eventsCorrect answer is option 'A'. Can you explain this answer?
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ample number of questions to practice According to the statistical definition of probability, the probability of an event A is thea)limiting value of the ratio of the no. of times the event A occurs to the number of times the experiment is repeatedb)the ratio of the frequency of the occurrences of A to the total frequencyc)the ratio of the frequency of the occurrences of A to the non-occurrence of Ad)the ratio of the favourable elementary events to A to the total number of elementary eventsCorrect answer is option 'A'. Can you explain this answer? tests, examples and also practice CA Foundation tests.
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