A variable of a population has a left-skewed distribution. a. If a large simple random sample is taken from the population, roughly what shape will the distribution of the sample have? Explain your answer.b. If two simple random samples are taken from the population, would you expect the two sample distributions to have identical shapes? Explain your answer.c. If two simple random samples are taken from the population, would you expect the two sample distributions to have similar shapes? If so, what shape would that be? Explain your answers.
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 variable of a population has a left-skewed distribution.
a. If a large simple random sample is taken from the population, roughly what shape will the distribution of the sample have? Explain your answer.
b. If two simple random samples are taken from the population, would you expect the two sample distributions to have identical shapes? Explain your answer.
c. If two simple random samples are taken from the population, would you expect the two sample distributions to have similar shapes? If so, what shape would that be? Explain your answers.
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