In a bank, the drive-in window is serviced by one teller, the data analysis led to the conclusion that: Inter-arrival times: exponentially distributed with rate A = 45/hour, and Service times: Normal(1.1, 0.22). Consider that 51 be the true mean value u0 = 51. There were 6 statistically independent replications of the model, each of 2-hour duration, and as in the following table. %3D (Replication, Arrival/arrival) : (1, 50), ( 2, 50) (3,50),(4,49),(5,49), (6 , 51) Compute the sample mean. Answer:
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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