A student wants to go to the gym, but it hard to find time bètween work and classes. Through observation, student has established a probability distribution of a time he will be able to attend gym during the week. P(x) 0.4 3 0.3 0.2 0.1 a. What is the highest limit of a probpbility function? b. What is the probability the student will be able to go to the gym more than 2 hours per week P(x > 2)?
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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