dealing with the life expectancy of light bulbs whose lifetimes are normally distributed with a mean life of 750 hours and with a standard deviation of 80 hours. Show or explain how you determine the appropriate z-score and related percentage. What percent of light bulbs will last longer than 870 hours? What percent of light bulbs will last between 730 hours and 850 hours?
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!
dealing with the life expectancy of light bulbs whose lifetimes are
- What percent of light bulbs will last longer than 870 hours?
What percent of light bulbs will last between 730 hours and 850 hours?
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