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by: Nelda Cronin

EnvironmentalAnalysis&Modelng IES612

Marketplace > Miami University > Environmental Science > IES612 > EnvironmentalAnalysis Modelng
Nelda Cronin
GPA 3.77


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Class Notes
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This 0 page Class Notes was uploaded by Nelda Cronin on Sunday November 1, 2015. The Class Notes belongs to IES612 at Miami University taught by A.Bailer in Fall. Since its upload, it has received 31 views. For similar materials see /class/233320/ies612-miami-university in Environmental Science at Miami University.


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Date Created: 11/01/15
0433 Wednesday July 14 2010 file manatee linreg adequacy 27jan04doc directory ClassesSpring 04 contents residual plots and related analysis data manatees input year nboats manatees cards 77 447 13 78 460 21 79 481 24 80 498 16 81 513 24 82 512 20 83 526 15 84 559 34 85 585 33 86 614 33 87 645 39 88 675 43 89 711 50 90 719 47 ODS RTF filequotZbaileraj2ClassesSpring 39O4manatee resid outputrtfquot NOTE output to DELL in 292 Bac proc reg model manatees nboats plot manateesnboats pnboats overlay plot rp plot nppr normal probability plot output outman7res7dat rresid pyhat run ODS RTF CLOSE proc univariate dataman7res7dat plot title 39Number of Manatees killed regressed on the number of boats registered in Florida39 var resid id year run 0433 Wednesday July 14 2010 imported file manatee resid outputrtf Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr gt F Model 1 171197866 171197866 9361 lt0001 Error 12 21944991 1828749 Corrected Total 13 193142857 Root MSE 427639 RSquare 08864 Dependent Mean 2942857 Adj RSq 08769 CoeffVar 1453141 Parameter Estimates Parameter Standard Variable DF Estimate Error tValue Prgtt 1 4143044 741222 559 00001 Intercept nboats 1 012486 001290 968 lt0001 0433 Wednesday July 14 2010 mnnuterss 7M H H W nbnuts 5D manutees x x x x x x x x x x x x 425 45D HS SDI 575 551 575 BED 525 BED E75 7I 775 nbnuts PM munultes nbnnks FRED anuls 0433 Wednesday July 14 2010 mnnuterss 7M H H W nbnuts 75 Hesiduu Preditiad Vu ua mnnuterss 7M H H W nbnuts 1 D I E f D E g L E g D 4 E D 2 D w w w w w w w w w BB I D3 M H5 15 D7 DE U9 1 Dumu ulm Disiribulinn DF Residual The UNIVARIATE Procedure Variable resid Residual Moments N 14 Sum Wei hts 14 Mean 6 Sum Observations 6 Std Deviation 416862647 Variance 168867622 Skewness 65789529 Kurtosis 662947163 Uncorrected SS 219449968 Corrected SS 219449968 Coeff Variation Std Error Mean 169867561 Basic Statistical Measures L cation Variability Mean 6666666 Std Deviation 416862 Median 0021722 Variance 1688076 Mode 1487956 ange Interquartile Range 488842 Tests for Location Mu00 Statistic p Value n Student39s t t e Pr gt ItI 19999 39 e Pr gt IMI 1 9999 5 Sign M Signed Rank 5 4 Pr gt s 08077 Quantiles Definition 5 Quantile Estimate 100 Max 5632753 99 5632753 95 5632753 90 5371965 75 Q 2 653776 50 Median 0 021722 2 234640 750684 5 9246811 1 9246811 0 Min 9246811 Number of Manatees killed regressed on the number of boats registered in Florida 12 The UNIVARIATE Procedure Variable resid Residual Extreme Observations L u39eh Value year Obs Value year Obs 924681 83 7 138635 85 9 4 75068 80 4 265378 89 13 249875 82 6 499406 78 2 2 23464 86 10 537196 79 3 1 38274 77 1 563275 84 8 Stem Leaf Boxplot 4 946 3 7 1 0 144 3 e 431 3 2 52 2 4 s 1 6 I 8 2 1 Normal Probability Plot 5 I I I I I I 9 2 1 6 1 2 Week 72IES 612STA 45735TA 4576doc IE5 612STA 4 573STA 4 576 Winfer 2009 l MulTiple Comparisons Suppose you rejecT The overall hypoThesis H0 in Hz p3 HT WhaT nexT Which means differ t A t Linear combinaTion Zaip1 which is esTimaTed by z Zaiyi This linear combinaTion is called a 39 i1 I1 t CONTRAST if Zai 0 Suppose T4 populaTions Example 1 The conTrasT for comparing Two means p1 Hz is The conTrasT of The difference of t The Two means in H2 Zaire 1 1 1H2 0 3 0 i1 Example 2 ConTrasT for comparing The mean of one populaTion wiTh The average of Two oTher populaTion means us This can be wriTTen as a The conTrasT t 1 1 Z Zaiui 1Iu1 1 2i13 0P4 EIu1 3 1P3 0P4 i1 You can TesT hypoTheses abouT conTrasTs t Ho g Zaipi 0 i1 t H X Zaipi 3 0 i1 A2 TS F E where 880 4 wiTh pvalue PrF1n it gt Fobs SE T obs M Zaf ni i1 l l l I I Two conTrasTs 1 Zaipi and 2 Zbip1 are ORTHOGONAL if 0 i1 i1 39 39 TreaTmenT SS can be parTiTioned inTo T1 muTually orThogonal conTrasTs CUsersbailerajBAILERAJClassesWebCLASSESies612lecTuresWeek 72IES 612STA 457622feb09doc 2222009 1 I Example The MeaT sTudy wiTh using logCounTs I Using R Consider The following conTr asTs 1 Compare The mean log BacTer ia counT for CO2 To The mean log BacTer39ia counT for The plasTic condiTion WhaT would This conTr asT look like N Compare The mean log BacTer ia counT for CO2 To The mean log BacTer39ia counT for The mixed condiTion WhaT would This conTr asT look like A Compare The mean log BacTer ia counT for CO2 To The mean log BacTer39ia counT for The vacuum condiTion WhaT would This conTr asT look like CUsersbailerajBAILERAJClassesWebCLASSESies612lecTuresWeek 72I ES 612STA 457622feb09doc 2222009 2 4 Compare The mean log BacTer ia counT for plasTic To The average mean log BacTer39ia counT for The oTher Thr ee condiTions WhaT would This conTr asT look like OK so how do we do This on R We fir sT need To fiT The Means Model so WiTh MeatBacteria The acTive daTa seT using RCommander Statistics gt Fit Models gt Linear model Linear Model E nter name for model M eatM eansAN UW I Vatiables doubleclick to formula A V 1 Model Formula I log ount quot lCondition l Subset expression lta valid casesgt UK I Cancel I Help Now we can obTain conTr asTs of The means using This Means model CUsersbuilerajBAILERAJClussesWebCLASSESies612lecTLIresWeek 72I ES 612STA 457622feb09doc 2222009 3


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