实验吧-线回归与卡方分析.doc

实验八 卡方分析与线性回归 植保133 裴小津 2013010320data abc;do a=1 to 2;do b= 1 to 2;input c;output ;end ;end;cards;26 184 50 200proc freq;weight c;tables a*b/chisq expected nopercent nocol;run;The SAS System 00:19 Sunday, January 1, 2006 1 The FREQ Procedure Table of a by b a b Frequency Expected Row Pct 1 2 Total 1 26 184 210 34.696 175.3 12.38 87.62 2 50 200 250 41.304 208.7 20.00 80.00 Total 76 384 460 Statistics for Table of a by b Statistic DF Value Prob Chi-Square 1 4.8037 0.0284 Likelihood Ratio Chi-Square 1 4.8944 0.0269 Continuity Adj. Chi-Square 1 4.2671 0.0389 Mantel-Haenszel Chi-Square 1 4.7932 0.0286 Phi Coefficient -0.1022 Contingency Coefficient 0.1017 Cramers V -0.1022 Fishers Exact Test Cell (1,1) Frequency (F) 26 Left-sided Pr = F 0.9903 Table Probability (P) 0.0091 Two-sided Pr |r| under H0: Rho=0 x y x 1.00000 -0.83714 0.0049 y -0.83714 1.00000 0.0049data new;infile D:shuju.txt;input x1 x2 y;proc corr nosimple;var x1 x2 y;run;The SAS System 01:37 Sunday, January 1, 2006 10 The CORR Procedure 3 Variables: x1 x2 y Pearson Correlation Coefficients, N = 13 Prob |r| under H0: Rho=0 x1 x2 y x1 1.00000 -0.71738 0.62939 0.0058 0.0212 x2 -0.71738 1.00000 0.01347 0.0058 0.9652 y 0.62939 0.01347 1.00000 0.0212 0.9652data new;input x y;cards;35.5 12 34.1 16 31.7 9 40.3 2 36.8 7 40.2 3 31.7 13 39.2 9 44.2 -1proc reg;model y=x;proc glm;model y=x;run;The SAS System 01:06 Sunday, January 1, 2006 6 The GLM ProcedureDependent Variable: y Sum of Source DF Squares Mean Square F Value Pr F Model 1 174.8887762 174.8887762 16.40 0.0049 Error 7 74.6667793 10.6666828 Corrected Total 8 249.5555556 R-Square Coeff Var Root MSE y Mean 0.700801 41.99128 3.265989 7.777778 Source DF Type I SS Mean Square F Value Pr F x 1 174.8887762 174.8887762 16.40 0.0049 Source DF Type III SS Mean Square F Value Pr F x 1 174.8887762 174.8887762 16.40 0.0049 Standard Parameter Estimate Error t Value Pr |t| Intercept 48.54931936 10.12778626 4.79 0.0020 x -1.09962204 0.27156710 -4.05 0.0049data new;input x y;l=log(y/(1-y);m=log(1/(1-y);g=log(1/log(1/y);cards;1 0.00043 5 0.0049 12 0.0087 17 0.016 24 0.05130 0.117 36 0.217 42 0.415 50 0.765 56 0.80proc reg;model y l m g=x;run;The SAS System 01:06 Sunday, January 1, 2006 7 The REG Procedure Model: MODEL1 Dependent Variable: y Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr F Model 1 0.72626 0.72626 36.02 0.0003 Error 8 0.16131 0.02016 Corrected Total 9 0.88757 Root MSE 0.14200 R-Square 0.8183 Dependent Mean 0.23950 Adj R-Sq 0.7955 Coeff Var 59.28848 Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr |t| Intercept 1 -0.17319 0.08213 -2.11 0.0680 x 1 0.01512 0.00252 6.00 0.0003 The SAS System 01:06 Sunday, January 1, 2006 8 The REG Procedure Model: MODEL1 Dependent Variable: l Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr F Model 1 76.10235 76.10235 288.19 |t| Intercept 1 -6.81696 0.29721 -22.94 .0001 x 1 0.15474 0.00912 16.98 F Model 1 2.48210 2.48210 21.24 0.0017 Error 8 0.93477 0.11685 Corrected Total 9 3.41687 Root MSE 0.34183 R-Square 0.7264 Dependent Mean 0.40454 Adj R-Sq 0.6922 Coeff Var 84.49873 Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr |t| Intercept 1 -0.35840 0.19770 -1.81 0.1074 x 1 0.02795 0.00606 4.61 0.0017 The SAS System 01:06 Sunday, January 1, 2006 10 The REG Procedure Model: MODEL1 Dependent Variable: g Ana