a. The variance of a data set is zero or negative when: i all the data is negative ii there are more negative data points than positive iii the mean is less than the median iv the data is left-skewed v all the above vi none of the above b. A distribution is positively skewed when: i the mean is larger than the median ii the mean is smaller than the median iii the mean and median are equal iv all of the above v none of the above
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. The variance of a data set is zero or negative when:
i all the data is negative
ii there are more negative data points than positive
iii the
iv the data is left-skewed
v all the above
vi none of the above
b. A distribution is positively skewed when:
i the mean is larger than the median
ii the mean is smaller than the median
iii the mean and median are equal
iv all of the above
v none of the above
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