Solution to Practice Quiz 2

The full quiz is here.  The answers appear below.  Comments, which are not part of the answers, are italicized.

For the batch {1, 2} compute the

  1. Mean: (1+2)/2 = 1.5.
  2. Five-letter summary: N=2, so the order of the median is 1h and the depths of the hinges are (1h + 1)/2 = 1.  Whence median = 1.5, upper hinge = maximum = 2, lower hinge = minimum = 1, and h-spread = range = 1.  (Arrange these in the usual way to exhibit the 5-letter summary.)
  3. Standard deviation: sqrt(variance) = sqrt(0.5) = 0.71, approx.  (see #4).
  4. Variance: [(1-1.5)2 + (2-1.5)2]/(2-1) = 0.5.
  5. Skewness (use the method of moments estimator): The mm estimator of variance is 0.25 (see #4 and use "2" in the denominator instead of "2-1"), so the mm sd is sqrt(0.25) = 0.5.  The standardized values are therefore {(1-1.5)/0.5, (2-1.5)/0.5} = {-1, 1}.  Their mean cube is 0.
  6. Kurtosis (use the method of moments estimator): the fourth powers of the standardized values are 1, so their mean is 1.
  7. MAD: the absolute deviations from the median are {0.5, 0.5}; the median of this set is 0.5.
  8. Geometric mean: sqrt(1*2) = sqrt(2) = 1.41, approx.
  9. 25% trimmed mean: trimming does not remove anything from this batch because N=2 and 25% of 2 is 0.5, which is less than 1.  Therefore the trimmed mean is the mean, which is 1.5.

Consider the batches A = {0, 1, -1}, B = {0, 1, 3}, C = {0, 1, 10}, D = {100, 200, 300}, E = {100, 200, 400}, F = {0, 9, 10}, and G = {1000, 1000, 1000}.

  1. Order the batches from least to greatest variance.
    The variance is unchanged when a constant is added to all values, so the variance of A is the variance of {0, 1, 2}.  Fixing the first two values and increasing the maximum must increase the variance, so A < B < C.  Similar reasoning gives D < E.  Negating the values will not change the variance, either, so negating all values in F and adding 10 demonstrates F = C.  The variance of D must be 100*100 times the variance of {1, 2, 3}, which has the same variance as A (just subtract 2 from each value).  Clearly this is much larger than the variance of A, B, C, or F.  Finally, the variance of G is zero since all values are the same, but all other variances are greater than zero.  Therefore:
    G < A < B < C = F < D < E.
  2. Order the batches from least to greatest skewness.
    Evidently F has negative skewness and the skewness of G is not defined.  All the other skewnesses are positive.  Use the same reasoning as in #10, but note that skewness depends only on standardized values in a batch: that is, it is unchanged when a all values are rescaled or shifted by a constant.  We can rescale and shift D to A (multiply by 0.01 and add -2) and E to B (multiply by 0.01 and add -1).  Therefore
    F < A = D < B = E < C.
  3. Order the batches from least to greatest kurtosis.
    The reasoning is the same as in #11, except to note that F cannot have negative kurtosis; instead, it must have the same kurtosis as C.  Therefore the correct order is
    A = D < B = E < C = F.

General comments

A good way to understand mathematical formulas is to apply them to simple situations.  This is the kind of quiz you should give yourself whenever you encounter a new statistic: that is, ask what its values are for some very simple batches..

The answers to questions 10-12 show how some basic properties of variance, skewness, and kurtosis can be used to simplify calculations and estimate values.  These properties are:

Adding a constant to all values in a batch ("shifting") does not change these statistics.
Multiplying all values in a batch by a constant ("rescaling") does not change skewness or kurtosis.  Indeed, shifting and rescaling do not change any statistic that depends only on the standardized batch values.
Multiplying all values in a batch by a constant a multiplies the variance by a2 (and therefore multiplies the standard deviation by |a|).  This is true regardless of the formula used for variance (because the two formulas differ by a factor that depends only on N, not on the data themselves).

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