07e-MReg-phosphorus

07e-MReg-phosphorus - EXST7015 :Statistical Techniques II...

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EXST7015 :Statistical Techniques II Geaghan Multiple (Linear) Regression Introductory example Page 1 07e-MReg-phosphorus.docs 1 options ps=256 ls=132 nocenter nodate nonumber; 3 DATA ONE; 4 TITLE1 'EXST7015: Multiple Regression from Snedecor & Cochran (1967)'; 5 INPUT X1 X2 X3 Y; 6 **** LABEL Y ='Plant available phosphorus' 7 X1='Inorganic phosphorus' 8 X2='Hydrolized organic phosphorus' 9 X3='Nonhydrolized phosphorus'; 10 CARDS; NOTE: The data set WORK.ONE has 18 observations and 4 variables. NOTE: DATA statement used: real time 0.05 seconds cpu time 0.05 seconds 10 ! RUN; 29 ; 30 PROC PRINT DATA=ONE; TITLE2 'RAW DATA LISTING'; RUN; NOTE: There were 18 observations read from the data set WORK.ONE. NOTE: The PROCEDURE PRINT printed page 1. NOTE: PROCEDURE PRINT used: real time 0.04 seconds cpu time 0.04 seconds EXST7015: Multiple Regression from Snedecor & Cochran (1967) RAW DATA LISTING Obs X1 X2 X3 Y 1 0.4 53 158 64 2 0.4 23 163 60 3 3.1 19 37 71 4 0.6 34 157 61 5 4.7 24 59 54 6 1.7 65 123 77 7 9.4 44 46 81 8 10.1 31 117 93 9 11.6 29 173 93 10 12.6 58 112 51 11 10.9 37 111 76 12 23.1 46 114 96 13 23.1 50 134 77 14 21.6 44 73 93 15 23.1 56 168 95 16 1.9 36 143 54 17 26.8 58 202 168 18 29.9 51 124 99 31 PROC REG DATA=ONE ALL LINEPRINTER; TITLE2 'PROC REG OUTPUT WITH ALL OPTIONS'; 32 MODEL Y = X1 X2 X3 / INFLUENCE; 33 TEST X1=2; TEST X1=X2=X3; 34 RUN; NOTE: 18 observations read. NOTE: 18 observations used in computations. 34 ! OPTIONS PS=60 LS=120; 35 MODEL Y = X1 X2 X3 / PARTIAL; 36 PLOT RESIDUAL.*PREDICTED. / VREF=0; 37 RUN; 38 OPTIONS LS=80; NOTE: The PROCEDURE REG printed pages 2-20. NOTE: PROCEDURE REG used: real time 0.13 seconds cpu time 0.13 seconds
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EXST7015 :Statistical Techniques II Geaghan Multiple (Linear) Regression Introductory example Page 2 07e-MReg-phosphorus.docs EXST7015: Multiple Regression from Snedecor & Cochran (1967) PROC REG OUTPUT WITH ALL OPTIONS The REG Procedure Descriptive Statistics Uncorrected Standard Variable Sum Mean SS Variance Deviation Intercept 18.00000 1.00000 18.00000 0 0 X1 215.00000 11.94444 4321.02000 103.11556 10.15458 X2 758.00000 42.11111 35076 185.63399 13.62476 X3 2214.00000 123.00000 307894 2092.47059 45.74353 Y 1463.00000 81.27778 131299 728.80065 26.99631 Uncorrected Sums of Squares and Crossproducts Variable Intercept X1 X2 X3 Y Intercept 18 215 758 2214 1463 X1 215 4321.02 10139.5 27645 20706.2 X2 758 10139.5 35076 96598 63825 X3 2214 27645 96598 307894 187542 Y 1463 20706.2 63825 187542 131299 Correlation Variable X1 X2 X3 Y X1 1.0000 0.4616 0.1520 0.6934 X2 0.4616 1.0000 0.3175 0.3545 X3 0.1520 0.3175 1.0000 0.3617 Y 0.6934 0.3545 0.3617 1.0000 Model Crossproducts X'X X'Y Y'Y Variable Intercept X1 X2 X3 Y Intercept 18 215 758 2214 1463 X1 215 4321.02 10139.5 27645 20706.2 X2 758 10139.5 35076 96598 63825 X3 2214 27645 96598 307894 187542 Y 1463 20706.2 63825 187542 131299 X'X Inverse, Parameter Estimates, and SSE Variable Intercept X1 X2 X3 Y Intercept 0.8133156545 0.0019185269 -0.011398244 -0.002444578
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This note was uploaded on 12/29/2011 for the course EXST 7087 taught by Professor Wang,j during the Fall '08 term at LSU.

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07e-MReg-phosphorus - EXST7015 :Statistical Techniques II...

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