Modeling Hydrologic Change: Statistical Methods - Chapter 9 pot

... 0.0426 0 .99 50 1 .92 6 4.262 18283 0 0.0050 0. 190 0 0.0476 0 .99 80 2.057 4. 299 198 97 1 0.0030 0.1140 37/38 0.0243 0 .99 90 2.141 4.322 21006 0 0.0010 0.0380 0.0253 0 .99 95 2.213 4.343 22005 0 0.0005 0.0 190 ... 1 .90 00 0.02 89 0 .96 00 1.4 89 4.140 13788 0 0.0100 0.3800 0.03 89 0 .97 50 1.611 4.174 1 491 8 0 0.0150 0.5700 0.05 39 0 .98 00 1.663 4.188 15428 0 0.0050 0. 190 0 0.05 89...

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... 95 2 + 23 0 .99 6 499 8 90 3 1670 + 24 0 .99 894 88 418 824 + 25 0 .99 97325 5 49 702 + 26 0 .99 994 35 686 1 490 + 27 0 .99 999 04 1320 1600 + 28 0 .99 999 87 850 800 − 29 0 .99 999 99 614 3330 + 30 1.0000000 1720 1540 ... River 192 4– 195 5 195 7– 198 8 Symbol No. of ++ ++ Symbols Cumulative Probability 1280 795 − 98 0 1760 + 20 0 .94 490 79 741 806 + 21 0 .97 494 88 1630 1 190 − 2...

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... H., 194 1 Modeling hydrologic change: statistical methods / Richard H. McCuen. p. cm. Includes bibliographical references and index. ISBN 1-5 667 0-6 0 0 -9 1. Hydrologic models. 2. Hydrologic Statistical ... Problems Chapter 9 Detection of Change in Distribution 9. 1 Introduction 9. 2 Chi-Square Goodness-of-Fit Test 9. 2.1 Procedure 9. 2.2 Chi-Square Test for a No...

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... 1.0 1 0 .99 9 0.0126 0.035 −0.0 194 0 .99 89 2 0 .99 8 0.0243 0.068 −0.0385 0 .99 59 3 0 .99 5 0.0356 0.101 −0.0575 0 .99 19 4 0 .99 1 0.0465 0.134 −0.0765 0 .98 70 5 0 .98 6 0.0568 0.166 −0. 095 3 0 .98 10 6 0 .98 0 0.0666 ... Lake (October 198 8 to August 199 4). Y Record High 4,211.85 feet June 3–8, 198 6, and April 1–15, 198 7 Record Low 4, 191 .35 feet October-November 196 3 198 9...

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... of a hypothesis test. 3-1 1 Develop one-tailed upper, one-tailed lower, and two-tailed hypotheses related to the hydrologic effects of afforestation. 3-1 2 Develop one-tailed upper, one-tailed ... exact. 3.5 PROBLEMS 3-1 What are the characteristics of a null hypothesis and an alternative hypoth- esis? 3-2 Why is it necessary to state the null hypothesis as a finding of no si...

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... P Year P 195 4 6.43 195 8 3. 59 196 2 4.56 196 7 5. 19 195 5 5.01 195 9 3 .99 196 3 5.26 196 8 6.55 195 6 2.13 196 0 8.62 196 4 8.51 196 9 5. 19 195 7 4. 49 196 1 2.55 196 5 3 .93 197 0 4. 29 196 6 6.20 197 1 5.43 Year ... E Year E 195 4 8.30 195 8 8. 39 196 2 8.05 196 7 6.16 195 5 7.74 195 9 7 .94 196 3 8.03 196 8 7.44 195 6 6.84 196 0 9. 24 196 4 6 .91 196 9 9. 19 195 7 8.45 1...

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... 2221 196 8 2 890 2 890 193 7 2400 2814 195 3 2310 2331 196 9 2540 2540 193 8 1720 2015 195 4 1 290 1303 197 0 3700 3700 193 9 1000 1172 195 5 197 0 199 0 197 1 1240 1240 194 0 194 0 2186 195 6 298 0 3005 197 2 3166 ... 197 2 3166 3166 194 1 1201 1353 195 7 2740 2764 197 3 198 5 198 5 194 2 2780 3026 195 8 2781 2805 197 4 3180 3180 194 3 193 0 2110 195 9 98 5 99 6 197 5 2070 2070 19...

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... 3 198 7 5.2 4.6 0.6 4 198 8 6.3 5.2 1.1 6 198 9 4.3 2.4 1 .9 7 199 0 4 .9 2.7 2.2 8 199 1 5 .9 3.4 2.5 10 199 2 3.5 1.2 2.3 9 199 3 6.7 4.0 2.7 11 S p = 63 S n = 3 L1600_Frame_C08.fm Page 194 Tuesday, September ... 0.001 59 0.00171 2 0.0 095 2 0.01123 3 0.03 491 0.04614 4 0.08728 0.13342 5 0.15711 0. 290 53 6 0.2 094 7 0.50000 7 0.2 094 7 0.7 094 7 8 0.15711 0.86658 9 0.08728...

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... n 191 1 4 191 9 2 192 7 5 193 5 3 194 3 6 191 2 3 192 0 2 192 8 2 193 6 5 194 4 1 191 3 4 192 1 2 192 9 3 193 7 2 194 5 2 191 4 3 192 2 3 193 0 1 193 8 4 194 6 7 191 5 1 192 3 3 193 1 2 193 9 2 194 7 3 191 6 5 192 4 2 193 2 ... −0. 490 2.023 105 194 1 59 1.771 3 −0.067 1 .96 6 92 194 2 127 2.104 4 −1.283 2.1 29 135 194 3 94 1 .97 3 5 0.473 1. 894 78 194 4 66 1.820 6 −0.203 1 .9...

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... 0 .99 87 0 .99 87 0 .99 88 0 .99 88 0 .99 89 0 .99 89 0 .99 89 0 .99 90 0 .99 90 3.1 0 .99 90 0 .99 91 0 .99 91 0 .99 91 0 .99 92 0 .99 92 0 .99 92 0 .99 92 0 .99 93 0 .99 93 3.2 0 .99 93 0 .99 93 0 .99 94 0 .99 94 0 .99 94 0 .99 94 0 .99 94 0 .99 95 ... 0 .99 94 0 .99 95 0 .99 95 0 .99 95 3.3 0 .99 95 0 .99 95 0 .99 95 0 .99 96 0 .99 96 0 .99 96 0 .99 96 0 .99 96 0 .99 96 0 .99 97 3.4 0 ....

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