The following data were used to construct the histograms of the number of days required to fill orders for Company A, and Company B. Company A 9 7. 9. 10 10 9. 10 9. 10 10 Company B 8. 11 5. 10 9. 8. 15 12 Company A Company B 0.9- 0.9 0.8- 0.8 0.7 0.7- 0.6- 0.6 0.5- 0.5- 0.4- 0.4 0.3 0.3 0.2 0.2 0.1- 0.1- 7 8 9 10 11 12 13 5 6 7 89 10 11 12 13 14 15 16 17 Number of Working Days Number of Working Days Use the range and standard deviation to support the previous observation that Company A provides the more consistent and rellable delivery times. Compute the range and standard deviation of the number of days required to fill orders for Company A. (Round your answers to two decimal places.) range v days standard deviation 1.33 X days Compute the range and standard deviation of the number of days required to fill orders for Company B. (Round your answers to two decimal places.) range 10 v days standard deviation 3.05 X days Relative Frequency 8, 7. Relative Frequency
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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