Probability is the relative frequency with which an event occurs. These measures

Question

Probability is the relative frequency with which an event occurs. These measures help managers make educated decisions for their companies. Learning Objectives: Describe the types of probability: Empirical Probability is determined by observation. for example, the number of defects in 10,000 widgets was observed to be 25. So, P(defective) = 25/10,000. Subjective Probability- Subjective probability measures the likelihood of an event subjectively Rationally derived from knowledge and experience, A "personal belief' allowing substantial variation in estimates. Based on my experience and conditions of the present, I feel that the probability of candidate A winning the election is about 55%. Classical Probability - Classical probability involves enumerating all possible outcomes, counting the number of outcomes of interest, and computing probability of the outcomes of interest = number of the outcomes of interest/the total number of outcomes. If there are 40 even numbers and 60 odd numbers randomly distributed in a box, the probability of drawing an even number, P(even) =0.40. Learning Objective: What are the probability rules? Probability of an outcome can take any value from 0(0%, impossible) to 1(100%, certainty). the probability of all possible outcomes is 100%. An event consists of 1 or more outcomes. the probability of an event occurring is 1 minus the probability that it doesn't occur. Highlight the values which are NOT VALID for probabilities 0 50 -0.10 1.10 the Law of Large Numbers means that as the number of observations of an event becomes larger, the running mean of the relative frequency of the event appears to settle down to a constant value, the probability of the event. You have just flipped a fair coin 7 times getting all heads. Does the coin owe you a tail? Although the mythical Law of Averages predicts you are due for a tail, no, the probability of a head on the next toss hasn't changed. Is a good hitter in baseball who has struck of the last six times due for a hit his next time up? Yes, the hitter is due for a hit This is an example of the Law of Averages This is an example of the so-called Law of Averages. No. the hitter is not due for a hit because the Law of Averages is non-existent and doesn't predict anything. Yes. the hitter is due for a hit. This is an example of the Law of Large Numbers the Law of Large Numbers predicts the hitter is not due for a hit. the running mean of the relative frequency of the event appears to settle down to a constant value. This is an example of the Law of Large Numbers. This is an example of the Law of Averages.

Explanation / Answer

1) Since probability always lies between 0 to 1, -0.10 and 1.10 are not valid

2) Option b is correct. . Law of averages does not predict anything.

3) This an example of law of large numbers

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