When a man observed a sobriety checkpoint conducted by a police department, he saw 667 drivers were screened and 4 were arrested for driving while intoxicated. Based on those results, we can estimate that P(W) = 0.00600, where W denotes the event of screening a driver and getting someone who is intoxicated. What does P (W) denote, and what is its value? What does P(W) represent? O A. P(W) denotes the probability of a driver passing through the sobriety checkpoint. O B. P(W) denotes the probability of driver being intoxicated. O C. P(W) denotes the probability of screening a driver and finding that he or she is not intoxicated. O D. P(W) denotes the probability of screening a driver and finding that he or she is intoxicated. P(W) =D (Round to five decimal places as needed.)
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
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