12) Classify the random variable (RV) to be discrete, continuous or neither. In each case provide one possible value of the random variable. i) Waiting time until a specific bank goes bankrupt. iii) Number of eggs laid by a female logger head sea turtle. v) Difference of actual versus the advertized arrival time of a flight. vii) Amount of soda in a randomly select can which is supposed to have 12 fluid ounces. ix) Number of wing flaps (to the nearest integer) per minute of a humming bird. D stands for Discrete, C stands for Continuous and N stands for Neither) Not a RV D (19.2 years) N (19.2 years) C (19.2 years) Cannot be determined (i- Select One) D (50 eggs) C (50 eggs) N (50 eggs) Not a RV Cannot be determined (iii- Select One) Cannot be determined Not a RV N (10.3 min) D (10.3 min) C (10.3 min) (v- Select One)
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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