A study is hold for two types of light bulbs. Length of their lives in hours was measured and other conditions were kept constant. 50 experiments were conducted for light bulb-A and it was detected that the average length of life of it is 725 hours with the 10 hours standard deviation while 100 experiments were held for light bulb-B with the result of 800 hours average length of life and 50 hours standard deviation. If µA and µB are population means of life lengths of light bulb A and B respectively, find %90 confidence interval of µB-µA.
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!
A study is hold for two types of light bulbs. Length of their lives in hours was measured and other conditions were kept constant. 50 experiments
were conducted for light bulb-A and it was detected that the average length of life of it is 725 hours with the 10 hours standard deviation while 100
experiments were held for light bulb-B with the result of 800 hours average length of life and 50 hours standard deviation. If µA and µB are
population means of life lengths of light bulb A and B respectively, find %90 confidence interval of µB-µA.
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