Personnel at an Engineering company use an online terminal to make routine engineering calculations. If the time each engineer spends in a session at a terminal has an exponential density function with expected value of 36 minutes, calculate the following. 1. If an engineer has already been at the terminal for 30 minutes, what is the probability that he or she will spend more than another hour at the terminal? 2. Ninety percent of the sessions end in less than R minutes. What is R?
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!
Personnel at an Engineering company use an online terminal to make routine engineering calculations. If the time each engineer spends in a session at a terminal has an exponential density
1. If an engineer has already been at the terminal for 30 minutes, what is the probability that he or she will spend
more than another hour at the terminal?
2. Ninety percent of the sessions end in less than R minutes. What is R?
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