Weights of a certain product follow Normal Distribution with unknown parameters. Based on the past experience, we knew that 7.5% of all the products weigh less than 11.188 gr and 6% of all products weigh more than 18.0765 gr. Subject to the experience, calculate parameter values of the distribution.
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!
Weights of a certain product follow
parameters. Based on the past experience, we knew that 7.5% of all the
products weigh less than 11.188 gr and 6% of all products weigh more than
18.0765 gr. Subject to the experience, calculate parameter values of the
distribution.
Step by step
Solved in 3 steps with 3 images
