Two machines (A and B) are used to fill plastic bottles with liquid laundry detergent. By default, the variability of liquid filled should be in a normal distribution form and both machines should operate similarly. If there is any difference, they may need to be calibrated. The output below shows the production result obtained from 14 bottles of Machine A and 12 bottles of Machine B: LOOK TO THE 2 HOPTPS. Q) At the 10% significance level, test whether calibration need to be made or not.
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!
Two machines (A and B) are used to fill plastic bottles with liquid laundry detergent. By default, the variability of liquid filled should be in a
LOOK TO THE 2 HOPTPS.
Q) At the 10% significance level, test whether calibration need to be made or not.
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