"quantity"exercise: Sampling

A is correct. Sample selection bias often results when a lack of data availability leads to certain data being excluded from the analysis. Survivorship bias is an example of sample selection bias.

B is incorrect. Data mining bias relates to the overuse of the same or related data, i.e., searching for pattern. And survivorship bias is not an example of data mining bias.

C is incorrect. Look-ahead bias exists if the model uses data not available to the analyst at the time the analyst act on the model. Survivorship bias is not an example of look-ahead bias

A is correct. According to Chebyshev’s inequality, the proportion of the observations within k standard deviations of the arithmetic mean is at least 1 – 1/k2 for all k >1. For k = 3, that proportion is 1 – 1/32, which is 88.89%. The lower endpoint is, therefore, the mean (382) minus 3 times 14 (the standard deviation), and the upper endpoint is 382 plus 3 times 14 (i.e., 340 and 424, respectively).

C is incorrect; it is based on 2 standard deviations, not 3: 382 – 2 × 14 = 354 and 382 + 2 × 14 = 410.

B is incorrect; it centers the interval around the number of observations (438) rather than the mean (382)