A chemist knows that when he uses his 50 mL pipet therewill be some measurement error. The distribution of theerrors is very close to a normal distribution with a meanof 0.05 mL and a standard deviation of 0.01 mL. If thechemist measures out 150 mL by using this pipet threetimes and combining the quantities, the mean error willbe 0.15 mL. What’s the standard deviation of that error?A) 0.010 B) 0.017 C) 0.030D) 0.087 E) 0.090
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 chemist knows that when he uses his 50 mL pipet there
will be some measurement error. The distribution of the
errors is very close to a
of 0.05 mL and a standard deviation of 0.01 mL. If the
chemist measures out 150 mL by using this pipet three
times and combining the quantities, the mean error will
be 0.15 mL. What’s the standard deviation of that error?
A) 0.010 B) 0.017 C) 0.030
D) 0.087 E) 0.090
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