An assembly line produces flip flops of stated length 200 mm. The actual length of the flip flops are evenly distributed between 195 and 205 mm. What would the height of the probability distribution be? What is the probability that a flip flop is greater than 203 mm? What is the probability that the length of a flip flop is within 1 mm of the stated length?
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!
An assembly line produces flip flops of stated length 200 mm. The actual length of the flip flops are evenly distributed between 195 and 205 mm.
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