**4.1.** (v). **4.2.** (iii). **4.3.** Data are normally distributed. **4.4.** The probability plot and Shapiro–Wilk test both indicate that the data are normal. **4.5.** No. The RLs are probably too low to make a difference either way.

**5.1.** (d). **5.2.** (a). **5.** **3.** (iii). **5.4.** (A) Year 6 PCB data are normally distributed. Year 1 PCB data also are somewhat normal, but the probability plot shows deviations from a linear pattern in the upper and lower tails (i.e., the presence of large and small values); (B) The quantile–quantile plot suggests that the two data populations have roughly similar distributions, but the Year 1 PCB values are higher than the Year 6 values, while the side-by-side box plots show that the mean and median PCB for Year 1are larger than for Year 6; (C) The double quantile plot shows that the Year 1 PCBs are higher than the Year 6 values, for both the center and the tail portions of the distributions; (D) There is a downward trend in the PCB concentrations.

**6.1.** (v). **6.2.** (a). **6.3.** (d). **6.4.** Original data are right-skewed, with outliers, while the log-transformed data are normal (meaning the data are lognormally distributed), with no outliers. (A) Mean; (B) For the original data, the 25% trimmed mean of 16.6 is approximately equal to the median of 16; (C) The logarithms are normally distributed and the outliers “disappear.” **6.5.** The normal distribution fits the data better than the lognormal, but the reported value of 3.37 for ...

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