a) Which measures of central tendency do not exist for this data set? Choose all that apply. Mean Median Mode None of these measures (b) Suppose that the measurement 33 (the smallest measurement in the data set) were replaced by 26. Which measures of central tendency would be affected by the change? Choose all that apply. Mean Median Mode None of these measures (c) Suppose that, starting with the original data set, the largest measurement were removed. Which measures of central tendency would be changed from those of the original data set? Choose all that apply. Mean Median Mode None of these measures (d) Which of the following best describes the distribution of the original data? Choose only one. Negatively skewed Positively skewed Roughly symmetrical
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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