A Geiger counter counts the number of alpha particles from radioactive material. Over a long period of time, an average of 21 particles per minute occurs. Assume the arrival of particles at the counter follows a Poisson distribution. Find the probability that at least one particle arrives in a particular one second period. (Round your answer to four decimals. Be sure to note the units and convert, if necessary.) P(x ≥ 1) = Find the probability that at least two particles arrive in a particular 4 second period. (hint:this changes the mean) (Round your answer to four decimals.)
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!
Find the probability that at least one particle arrives in a particular one second period. (Round your answer to four decimals. Be sure to note the units and convert, if necessary.)
P(x ≥ 1) =
Find the probability that at least two particles arrive in a particular 4 second period. (hint:this changes the mean) (Round your answer to four decimals.)
P(x ≥ 2) =
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