A statistician developed a computer program to generate an Exponential Random variable. Each time the program is run, it generates a random number drawn from an Exponential distribution with parameter 1.7. The generated number, on each run of the program, is independent of how many times the program has been run. It is also independent of the numbers generated on previous runs of the program. (a) Someone runs the program 15 times. You guess that the number generated on the Sth run is greater than 3. What is the probability that you are right? Your answer correct up to four decimal places. (b) Someone runs the program 15 times. They tell you that the number generated on the Sth run is greater than 2. You guess that the number generated on this (5th) run is greater than 3. What is the probability that you are right? Your answer correct up to four decimal places. (c) What is the probability one will need to run the program more than 8 times before seeing a number greater than 3? Your answer correct up to four decimal places. (d) How many times will someone need to run the program until they expect to see a number greater than 3? Your answer correct up to four decimal places. (Non- integer answers are fine, do not round off!) (e) Someone runs the program 8 times. You guess that the maximum number generated during all these runs is greater than 3. What is the probability you are right? Your answer correct up to four decimal places. (f) Someone runs the program 8 times. They tell you that the number generated on the 5th run is less than 4. Then, you guess that the number generated on that (5th) run is greater than 3. What is the probability you are right? Your answer correct up to four decimal places.
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!
Step by step
Solved in 3 steps