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L1592_Frame_C15  Page 140  Tuesday, December 18, 2001  1:50 PM










                                           Pb (µg// //L)  Number     %        Cum. %
                                             0–0.9         20       0.143      0.143
                                             1–1.9         16       0.114      0.257
                                             2–2.9         32       0.229      0.486
                                             3–3.9         11       0.079      0.564
                                             4–4.9         13       0.093      0.657
                                             5–9.9         27       0.193      0.850
                                             10–14.9       7        0.050      0.900
                                             15–19.9       4        0.029      0.929
                                             20–29.9       6        0.043      0.971
                                             30–39.9       1        0.007      0.979
                                             40–49.9       1        0.007      0.986
                                             50–59.9       1        0.007      0.993
                                             60–69.9       0        0.000      0.993
                                             70–79.9       1        0.007      1.000
                                           Source: Prof. David Jenkins, University of California-Berkeley.
                        15.4 Rankit Regression. The table below gives eight ranked observations of a lognormally distrib-
                             uted variable y, the log-transformed values x, and their rankits.
                             (a) Make conventional probability plots of the x and y values. (b) Make plots of x and y versus
                             the rankits. (c) Estimate the mean and standard deviation. ND = not detected (<MDL).


                                y        ND      ND     11.6   19.4    22.9   24.6    26.8  119.4
                                x == == ln(y)  —  —      2.451  2.965   3.131  3.203   3.288  4.782
                                Rankit  −1.424  −0.852  −0.473  −0.153  0.153  0.473   0.852  1.424


                        15.5 Cohen’s Method — Normal. Use Cohen’s method to estimate the mean and standard deviation
                             of the n = 26 observations that have been censored at y c  = 7.


                                ND   ND   ND   ND    ND   ND   ND   ND   7.8   8.9  7.7  9.6   8.7
                                8.0  8.5  9.2  7.4   7.3  8.3  7.2  7.5  9.4   7.6  8.1  7.9  10.1


                        15.6 Cohen’s Method — Lognormal. Use Cohen’s method to estimate the mean and standard
                             deviation of the following lognormally distributed data, which has been censored at 10 mg/L.

                               14  15  16  ND   72  ND   12  ND   ND  20   52  16  25  33  ND   62


                        15.7 PCB in Sludge. Seven of the sixteen measurements of PCB in a biological sludge are below
                             the MDL of 5 mg/kg. Do the data appear better described by a normal or lognormal distri-
                             bution? Use Cohen’s method to obtain MLE estimates of the population mean and standard
                             deviation.


                               ND    ND   ND   ND    ND   ND   ND   6     10   12   16    16   17
                               19    37   41











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