/* Lesson 12-1 */ /* File Name = les1201.sas 01/12/06 */ data gakusei; infile 'all05be.prn' firstobs=2; input sex $ shintyou taijyuu kyoui jitaku $ kodukai carryer $ tsuuwa; if sex^='M' & sex^='F' then delete; proc print data=gakusei(obs=10); run; proc plot data=gakusei; : 散布図を描く plot shintyou*taijyuu; : 散布図の変量を指定(縦軸、横軸の順) plot taijyuu*shintyou; : run: : proc corr data=gakusei; : 相関係数(相関行列)を計算 run: :
SAS システム 2 17:36 Thursday, January 5, 2006 プロット : SHINTYOU*TAIJYUU. 凡例: A = 1 OBS, B = 2 OBS, ... (NOTE: 42 オブザベーションが欠損値です.) SHINTYOU | 200 + | | A B A 180 + A BECFDDBEA B B A A A | CAGELHTPJHCFECB BB | AFAGIIFEBBDEAA AA A A 160 + ADDGDIEDBABB | A ECAEDDA A A | A BAA 140 + ---+-----------+-----------+-----------+-----------+-- 20 40 60 80 100 TAIJYUU SAS システム 3 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*SHINTYOU. 凡例: A = 1 OBS, B = 2 OBS, ... (NOTE: 42 オブザベーションが欠損値です.) 100 + B | A A TAIJYUU | A A A B B A A | A B CBDDC DCGAD CCF B BA | A AA E B CBDBG KBRHLBLFFFD CBDCB A 50 + AAA CACEC EDIAG EBDGF DAABC BC | A A B D BA BA | | | 0 + --+-----------+-----------+-----------+-----------+-----------+- 140 150 160 170 180 190 SHINTYOU SAS システム 4 17:36 Thursday, January 5, 2006 Correlation Analysis 5 'VAR' Variables: SHINTYOU TAIJYUU KYOUI KODUKAI TSUUWA Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum SHINTYOU 327 167.8 8.1940 54880.7 145.0 186.0 TAIJYUU 296 58.5196 9.3328 17321.8 35.0000 100.0 KYOUI 108 86.4167 7.5407 9333.0 56.0000 112.0 KODUKAI 315 48314.3 48562.6 15219000 0 300000 TSUUWA 117 6783.4 4564.7 793652 0 30000.0 SAS システム 5 17:36 Thursday, January 5, 2006 Correlation Analysis Pearson Correlation Coefficients / Prob > |R| under Ho: Rho=0 / Number of Observations SHINTYOU TAIJYUU KYOUI KODUKAI TSUUWA SHINTYOU 1.00000 0.70509 0.37978 0.05216 0.04552 0.0 0.0001 0.0001 0.3624 0.6306 327 296 108 307 114 TAIJYUU 0.70509 1.00000 0.66154 -0.01649 0.01120 0.0001 0.0 0.0001 0.7839 0.9093 296 296 108 279 106 KYOUI 0.37978 0.66154 1.00000 -0.08519 -0.00489 0.0001 0.0001 0.0 0.3899 0.9788 108 108 108 104 32 KODUKAI 0.05216 -0.01649 -0.08519 1.00000 0.20394 0.3624 0.7839 0.3899 0.0 0.0295 307 279 104 315 114 TSUUWA 0.04552 0.01120 -0.00489 0.20394 1.00000 0.6306 0.9093 0.9788 0.0295 0.0 114 106 32 114 117
[注意] 相関行列は細切れに表示されるので、 不要部分を削除することによって整形しレポート等に使うこと。
/* Lesson 12-2 */ /* File Name = les1202.sas 01/12/06 */ data gakusei; infile 'all05be.prn' firstobs=2; input sex $ shintyou taijyuu kyoui jitaku $ kodukai carryer $ tsuuwa; if sex^='M' & sex^='F' then delete; proc print data=gakusei(obs=10); run; proc reg data=gakusei; : 回帰分析 model taijyuu=shintyou; : 変量を指定 output out=outreg1 predicted=pred1 residual=resid1; : 結果項目の保存 run; : : proc print data=outreg1(obs=15); : 表示してみる run; : : proc plot data=outreg1; : 散布図を描く plot taijyuu*shintyou/vaxis=20 to 100 by 20; : 体重と身長(縦軸指定) plot pred1*taijyuu; : 予測値と観測値 plot resid1*pred1 /vref=0; : 残差と予測値(残差解析)(水平軸指定) plot resid1*shintyou/vref=0; : 残差と説明変数(残差解析) plot resid1*taijyuu /vref=0; : 残差と目的変数(残差解析) run; : : proc univariate data=outreg1 plot normal; : 残差を正規プロットして確かめる var resid1; : run; :[補足] proc plot の下に以下の行を追加した方がより正確ではある。 欠損値を含むデータを解析対象から除外する事を指示する命令文である。 「欠損値です」の表示が無くなるだけで、得られる図は同じ(欠損値は描画できないから)。 試しに追加する/しないの両方で実行してみよ。
where shintyou^=. and taijyuu^=.;
SAS システム 2 17:36 Thursday, January 5, 2006 Model: MODEL1 Dependent Variable: TAIJYUU Analysis of Variance Sum of Mean Source DF Squares Square F Value Prob>F Model 1 12773.94489 12773.94489 290.662 0.0001 Error 294 12920.64146 43.94776 C Total 295 25694.58635 Root MSE 6.62931 R-square 0.4971 Dep Mean 58.51959 Adj R-sq 0.4954 C.V. 11.32836 SAS システム 3 17:36 Thursday, January 5, 2006 Parameter Estimates Parameter Standard T for H0: Variable DF Estimate Error Parameter=0 Prob > |T| INTERCEP 1 -78.107576 8.02313981 -9.735 0.0001 SHINTYOU 1 0.810528 0.04754164 17.049 0.0001 SAS システム 4 17:36 Thursday, January 5, 2006 S H T K C I A J O A T R N I K I D R S P E T J Y T U R U R S O S Y Y O A K Y U E I B E O U U K A E W D D S X U U I U I R A 1 1 1 F 145.0 38.0 . J 10000 . 39.4191 -1.4191 2 F 146.7 41.0 85 J 10000 Vodafone 6000 40.7970 0.2030 3 F 148.0 42.0 . J 50000 . 41.8506 0.1494 4 F 148.0 43.0 80 J 50000 DoCoMo 4000 41.8506 1.1494 5 F 148.9 . . J 60000 . 42.5801 . 6 F 149.0 45.0 . G 60000 . 42.6612 2.3388 7 F 150.0 46.0 86 40000 . 43.4717 2.5283 8 F 151.0 50.0 . G 60000 J-PHONE . 44.2822 5.7178 9 F 151.7 41.5 80 J 35000 . 44.8496 -3.3496 10 F 152.0 35.0 77 J 60000 DoCoMo 2000 45.0928 -10.0928 11 F 152.0 43.0 . J 20000 au 3500 45.0928 -2.0928 12 F 152.0 44.0 . 45000 DoCoMo 4000 45.0928 -1.0928 13 F 153.0 41.0 . J 125000 No . 45.9033 -4.9033 14 F 153.0 42.0 . G 0 Vodafone 1000 45.9033 -3.9033 15 F 153.0 46.5 87 G 10000 . 45.9033 0.5967 SAS システム 6 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*SHINTYOU. 凡例: A = 1 OBS, B = 2 OBS, ... (NOTE: 42 オブザベーションが欠損値です.) TAIJYUU | 100 + B | A A 80 + A A A B B A A | A B CBDDC DCGAD CCF B BA 60 + A AA E B CBDBG KBRHLBLFFFD CBDCB A | AAA CACEC EDIAG EBDGF DAABC BC 40 + A A B D BA BA | 20 + | --+-----------+-----------+-----------+-----------+-----------+- 140 150 160 170 180 190 SHINTYOU SAS システム 7 17:36 Thursday, January 5, 2006 プロット : PRED1*TAIJYUU. 凡例: A = 1 OBS, B = 2 OBS, ... (NOTE: 42 オブザベーションが欠損値です.) 80 + | PRED1 | A A B A | A BDACFAB F B A A A A | ABBCCBMHDEBHBB A BC 60 + CECLHGGKDIBAADABA A | AG EHCH CCAAE A | BADBDGACAAAA | BABEDCDA A A | A CABB B A 40 + A BA ---+------------+------------+------------+------------+-- 20 40 60 80 100 TAIJYUU SAS システム 8 17:36 Thursday, January 5, 2006 プロット : RESID1*PRED1. 凡例: A = 1 OBS, B = 2 OBS, ... (NOTE: 42 オブザベーションが欠損値です.) | R 50 + e | s | A A i 25 + A A d | A B A AB B A u | A A A B BBBB BCBEDCDE AB A A a 0 +-------------A-ABAA-CCCCFBDCJAEEBECHKBNHIJNCEBCH-A-AA------------ l | AA BAAAB BA BGDCACDFCFDCCAACBAA | A A -25 + ---+-----------+-----------+-----------+-----------+-----------+-- 30 40 50 60 70 80 Predicted Value of TAIJYUU SAS システム 9 17:36 Thursday, January 5, 2006 プロット : RESID1*SHINTYOU. 凡例: A = 1 OBS, B = 2 OBS, ... (NOTE: 42 オブザベーションが欠損値です.) | R 50 + e | s | A A i 25 + A A d | A B A A B B A u | A A A B B BBB B CBEDC CBD BA A A a 0 +--------A-A-BAA-C-DBCEC-DCJAE-EBECH-KBNFJAJGGCE-BCH-A--AA-------- l | A A BA AAB B A BFE CACDEACBDDC CABBB AA | A A -25 + ---+-----------+-----------+-----------+-----------+-----------+-- 140 150 160 170 180 190 SHINTYOU SAS システム 10 17:36 Thursday, January 5, 2006 プロット : RESID1*TAIJYUU. 凡例: A = 1 OBS, B = 2 OBS, ... (NOTE: 42 オブザベーションが欠損値です.) | R 50 + e | s | A A i 25 + A A d | A BABC A u | A ABABBBLBECGAC A A a 0 +--------------A-DBDFFEMKEQGJSRHLCH-E--------------------- l | A CABCI DLDIDDGCBB | A A -25 + ---+------------+------------+------------+------------+-- 20 40 60 80 100 TAIJYUU SAS システム 11 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Moments N 296 Sum Wgts 296 Mean 0 Sum 0 Std Dev 6.618065 Variance 43.79878 Skewness 1.45171 Kurtosis 4.288591 USS 12920.64 CSS 12920.64 CV . Std Mean 0.384667 T:Mean=0 0 Pr>|T| 1.0000 Num ^= 0 296 Num > 0 126 M(Sign) -22 Pr>=|M| 0.0123 Sgn Rank -2663 Pr>=|S| 0.0707 W:Normal 0.916044 PrSAS システム 15 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Histogram # Boxplot 35+* 1 * .* 4 0 .**** 14 0 .*************************** 107 +--+--+ .***************************************** 163 *-----* -15+** 7 | ----+----+----+----+----+----+----+----+- * may represent up to 4 counts SAS システム 16 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Normal Probability Plot 35+ * | * ** | *******++++ | ++************** | ********************** -15+**+***++++ +----+----+----+----+----+----+----+----+----+----+ -2 -1 0 +1 +2
[注意] 誤差は「説明変量」の軸と垂直に取ることに注意せよ。 誤差は測定時に混入していると考えてモデルが構築されているから。
[注意] 「正規性を乱している者は何でも除外してかまわない」というわけではない。 今回の場合は、元データに戻ったところ、体育会系のずんぐりした者であったため、 普通の大学生とは異なる性質を有していると判断し除外対象とした。 除外する場合にはその根拠を明確にしないと、「恣意的な解析」と言われかねないことに注意せよ。
/* Lesson 12-3 */ /* File Name = les1203.sas 01/12/06 */ data gakusei; infile 'all05be.prn' firstobs=2; input sex $ shintyou taijyuu kyoui jitaku $ kodukai carryer $ tsuuwa; if sex^='M' & sex^='F' then delete; if shintyou=. | taijyuu=. then delete; : 欠損値データを除外 proc print data=gakusei(obs=10); run; proc corr data=gakusei; where taijyuu<85; : 対象データを絞る run; proc reg data=gakusei; model taijyuu=shintyou; where taijyuu<85; : 対象データを絞る output out=outreg1 predicted=pred1 residual=resid1; run; proc print data=outreg1(obs=15); run; proc plot data=outreg1; where taijyuu<85; : 対象データを絞る plot taijyuu*shintyou; plot taijyuu*pred1; plot resid1*(pred1 shintyou taijyuu)/vref=0; : まとめて指定することも可 run; proc univariate data=outreg1 plot normal; var resid1; run;
SAS システム 2 17:36 Thursday, January 5, 2006 Correlation Analysis 5 'VAR' Variables: SHINTYOU TAIJYUU KYOUI KODUKAI TSUUWA Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum SHINTYOU 292 168.5 8.0976 49188.1 145.0 186.0 TAIJYUU 292 58.0421 8.4314 16948.3 35.0000 82.0000 KYOUI 105 85.9714 7.0485 9027.0 56.0000 110.0 KODUKAI 275 48925.5 50231.1 13454500 0 300000 TSUUWA 106 6966.5 4558.8 738452 0 30000.0 SAS システム 3 17:36 Thursday, January 5, 2006 Correlation Analysis Pearson Correlation Coefficients / Prob > |R| under Ho: Rho=0 / Number of Observations SHINTYOU TAIJYUU KYOUI KODUKAI TSUUWA SHINTYOU 1.00000 0.73303 0.34216 0.06174 0.00660 0.0 0.0001 0.0004 0.3077 0.9465 292 292 105 275 106 TAIJYUU 0.73303 1.00000 0.59461 0.00737 0.01120 0.0001 0.0 0.0001 0.9031 0.9093 292 292 105 275 106 KYOUI 0.34216 0.59461 1.00000 -0.07975 -0.00489 0.0004 0.0001 0.0 0.4279 0.9788 105 105 105 101 32 KODUKAI 0.06174 0.00737 -0.07975 1.00000 0.24950 0.3077 0.9031 0.4279 0.0 0.0110 275 275 101 275 103 TSUUWA 0.00660 0.01120 -0.00489 0.24950 1.00000 0.9465 0.9093 0.9788 0.0110 0.0 106 106 32 103 106 SAS システム 6 17:36 Thursday, January 5, 2006 Model: MODEL1 Dependent Variable: TAIJYUU Analysis of Variance Sum of Mean Source DF Squares Square F Value Prob>F Model 1 11115.76839 11115.76839 336.808 0.0001 Error 290 9570.96349 33.00332 C Total 291 20686.73188 Root MSE 5.74485 R-square 0.5373 Dep Mean 58.04212 Adj R-sq 0.5357 C.V. 9.89773 SAS システム 7 17:36 Thursday, January 5, 2006 Parameter Estimates Parameter Standard T for H0: Variable DF Estimate Error Parameter=0 Prob > |T| INTERCEP 1 -70.528696 7.01376139 -10.056 0.0001 SHINTYOU 1 0.763247 0.04158860 18.352 0.0001 SAS システム 10 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*SHINTYOU. 凡例: A = 1 OBS, B = 2 OBS, ... TAIJYUU | 100 + | | A 75 + A B AAA B C B BA A | BB B CBHCCADCGCD BCIAB BA | A AA E B C CBG JBMHKAKFEDD CAABA A 50 + AA CACEB DDGAF EBDGF DAABC BC | A A BA C BA BB A B A | A 25 + --+-----------+-----------+-----------+-----------+-----------+- 140 150 160 170 180 190 SHINTYOU SAS システム 11 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*PRED1. 凡例: A = 1 OBS, B = 2 OBS, ... TAIJYUU | 100 + | | A 75 + A B AAAB CBAB A | D BCBHCDDCGGBCIAB BA | A AA E BCCBGHDMJJKFEHCA CAA 50 + AABBCEBDDGAFEFGFCBABC BC | A ABA AD ABBA B A | A 25 + ---+-----------+-----------+-----------+-----------+-- 40 50 60 70 80 Predicted Value of TAIJYUU SAS システム 12 17:36 Thursday, January 5, 2006 プロット : RESID1*PRED1. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | i 20 + A A d | A AAABAA CAAA A u | A B B E BBBBABEAHBBDBD A B A a 0 +--A-ABAA-BABDEACCEAEE-EBHFDKGIIGFCDBCH-A-AA-------------- l | AB BBB E BABBFECBCEEBCBEBCABBBAA | A A C A -20 + ---+------------+------------+------------+------------+-- 40 50 60 70 80 Predicted Value of TAIJYUU SAS システム 13 17:36 Thursday, January 5, 2006 プロット : RESID1*SHINTYOU. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | i 20 + A A d | A AAABA A C B A A u | A B B E B BBBAB EAHBB DBD A AA A a 0 +--------A-A-BAA-B-BBCEA-CCEAE-E-EBH-HBKEJAIGFCD-BCH-A--AA-------- l | A B BB BAD B ABBFE DACEDACBBDC CABBB AA | A A C A -20 + ---+-----------+-----------+-----------+-----------+-----------+-- 140 150 160 170 180 190 SHINTYOU SAS システム 14 17:36 Thursday, January 5, 2006 プロット : RESID1*TAIJYUU. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | i 20 + A A d | A AAAA C BCA A u | B A D B AC DEDIBAFADB AA a 0 +----------A--AABBADADEFDFDDIFDIBRFKDEFCCC-E---------------------- l | ADA CDCH BBFEEEEDCAGC BAA | A B B A -20 + ---+---------+---------+---------+---------+---------+---------+-- 30 40 50 60 70 80 90 TAIJYUU SAS システム 15 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Moments N 292 Sum Wgts 292 Mean 0 Sum 0 Std Dev 5.734972 Variance 32.88991 Skewness 0.728763 Kurtosis 0.79055 USS 9570.963 CSS 9570.963 CV . Std Mean 0.335614 T:Mean=0 0 Pr>|T| 1.0000 Num ^= 0 292 Num > 0 125 M(Sign) -21 Pr>=|M| 0.0163 Sgn Rank -1793 Pr>=|S| 0.2150 W:Normal 0.961915 PrSAS システム 18 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Histogram # Boxplot 22.5+* 1 0 .* 3 0 .***** 13 0 .************ 35 | .************************* 73 +--+--+ .**************************************** 120 *-----* .************** 41 | -12.5+** 6 | ----+----+----+----+----+----+----+----+ * may represent up to 3 counts SAS システム 19 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Normal Probability Plot 22.5+ * | * ** | ******++++ | ********+ | ++******** | ************* | ***********+ -12.5+**+**+++ +----+----+----+----+----+----+----+----+----+----+ -2 -1 0 +1 +2
/* Lesson 12-4 */ /* File Name = les1204.sas 01/12/06 */ data gakusei; infile 'all05be.prn' firstobs=2; input sex $ shintyou taijyuu kyoui jitaku $ kodukai carryer $ tsuuwa; if sex^='M' & sex^='F' then delete; proc print data=gakusei(obs=10); run; proc reg data=gakusei; : 回帰分析 model taijyuu=shintyou kyoui; : 複数変量を指定 output out=outreg1 predicted=pred1 residual=resid1; : 結果項目の保存 run; : proc print data=outreg1(obs=15); run; : proc plot data=outreg1; : 散布図を描く where shintyou^=. and taijyuu^=. and kyoui^=.; : 解析に使ったデータのみ plot taijyuu*shintyou; : plot taijyuu*kyoui; : plot taijyuu*pred1; : 観測値と予測値 plot resid1*pred1 /vref=0; : 残差と予測値(残差解析) plot resid1*shintyou/vref=0; : 残差と説明変量(残差解析) plot resid1*kyoui /vref=0; : 残差と説明変量(残差解析) plot resid1*taijyuu /vref=0; : 残差と目的変量(残差解析) run; : : proc univariate data=outreg1 plot normal; : 残差を正規プロットして確かめる var resid1; : run; :
SAS システム 2 17:36 Thursday, January 5, 2006 Model: MODEL1 Dependent Variable: TAIJYUU Analysis of Variance Sum of Mean Source DF Squares Square F Value Prob>F Model 2 8833.42493 4416.71246 129.796 0.0001 Error 105 3572.95693 34.02816 C Total 107 12406.38185 Root MSE 5.83337 R-square 0.7120 Dep Mean 58.51296 Adj R-sq 0.7065 C.V. 9.96936 SAS システム 3 17:36 Thursday, January 5, 2006 Parameter Estimates Parameter Standard T for H0: Variable DF Estimate Error Parameter=0 Prob > |T| INTERCEP 1 -112.597020 11.05047954 -10.189 0.0001 SHINTYOU 1 0.693759 0.06936383 10.002 0.0001 KYOUI 1 0.637578 0.08084221 7.887 0.0001 SAS システム 4 17:36 Thursday, January 5, 2006 S H T K C I A J O A T R N I K I D R S P E T J Y T U R U R S O S Y Y O A K Y U E I B E O U U K A E W D D S X U U I U I R A 1 1 1 F 145.0 38.0 . J 10000 . . . 2 F 146.7 41.0 85 J 10000 Vodafone 6000 43.3716 -2.37160 3 F 148.0 42.0 . J 50000 . . . 4 F 148.0 43.0 80 J 50000 DoCoMo 4000 41.0856 1.91440 5 F 148.9 . . J 60000 . . . 6 F 149.0 45.0 . G 60000 . . . 7 F 150.0 46.0 86 40000 . 46.2986 -0.29858 8 F 151.0 50.0 . G 60000 J-PHONE . . . 9 F 151.7 41.5 80 J 35000 . 43.6525 -2.15251 10 F 152.0 35.0 77 J 60000 DoCoMo 2000 41.9479 -6.94790 11 F 152.0 43.0 . J 20000 au 3500 . . 12 F 152.0 44.0 . 45000 DoCoMo 4000 . . 13 F 153.0 41.0 . J 125000 No . . . 14 F 153.0 42.0 . G 0 Vodafone 1000 . . 15 F 153.0 46.5 87 G 10000 . 49.0174 -2.51744 SAS システム 6 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*SHINTYOU. 凡例: A = 1 OBS, B = 2 OBS, ... 100 + A | A A TAIJYUU | A A A | B BABAB AACAA A B A AA | A A B A B BBA BAGBC ABAA AABBA 50 + A A ADB CCE C BBACB A | A A B A A | | | 0 + --+-----------+-----------+-----------+-----------+-----------+- 140 150 160 170 180 190 SHINTYOU SAS システム 7 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*KYOUI. 凡例: A = 1 OBS, B = 2 OBS, ... 100 + A | A A TAIJYUU | AA A | A A C BBF BABA A A | A A C C AAF FBK AAA A 50 + A A AA D JCHBBA | A A B B | | | 0 + ---+-------+-------+-------+-------+-------+-------+-------+-- 50 60 70 80 90 100 110 120 KYOUI SAS システム 8 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*PRED1. 凡例: A = 1 OBS, B = 2 OBS, ... 100 + A | A A TAIJYUU | A A A | AAA BCABAB ABABAA A | A B BAAAAAAABBAAFEBABAA AB 50 + B CCABCCCC CEA B | AAAB A | | | 0 + --+-----------+-----------+-----------+-----------+-----------+- 40 50 60 70 80 90 Predicted Value of TAIJYUU SAS システム 9 17:36 Thursday, January 5, 2006 プロット : RESID1*PRED1. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | A i 20 + A d | A A A A u | A B BAAA AAA ABAAA A A a 0 +---A-AB---CCABBCBB-AABAAAABAAEDB-B---B-BAA---------A------------- l | A B AA BD B A AAAAABAAAAC A | -20 + ---+-----------+-----------+-----------+-----------+-----------+-- 40 50 60 70 80 90 Predicted Value of TAIJYUU SAS システム 10 17:36 Thursday, January 5, 2006 プロット : RESID1*SHINTYOU. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | A i 20 + A d | A A A A u | B B A BBBAB ABAA a 0 +----------A-A-A-A-AAACB-CBD-B-BABBC-A-DAB-BAC-A-C-A-A--A--------- l | A A AA B AAACB A BAA A A ACBA A | -20 + ---+-----------+-----------+-----------+-----------+-----------+-- 140 150 160 170 180 190 SHINTYOU SAS システム 11 17:36 Thursday, January 5, 2006 プロット : RESID1*KYOUI. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | A i 20 + A d | A A A A u | B A A B A C ABD B a 0 +-----------------------B-A-F-CDDKCBAH-A-BC---B--------A---------- l | AA B CA GACBD A B A | -20 + -+--------+--------+--------+--------+--------+--------+--------+- 50 60 70 80 90 100 110 120 KYOUI SAS システム 12 17:36 Thursday, January 5, 2006 プロット : RESID1*TAIJYUU. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | A i 20 + A d | AA A A u | A BAAAB B BBBA AA a 0 +----------------BABDCCFCAB-CFDCCAA-E----A---------------- l | A A BDABB CAADAAD A | -20 + ---+------------+------------+------------+------------+-- 20 40 60 80 100 TAIJYUU SAS システム 17 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Stem Leaf # Boxplot 2 4 1 * 1 8 1 0 1 01234 5 0 0 55567777788889 14 | 0 000001111112222334444 21 +--+--+ -0 4444443333333333333222222222222221111111111000 46 *-----* -0 9887777776666555555 19 | -1 0 1 | ----+----+----+----+----+----+----+----+----+- Multiply Stem.Leaf by 10**+1 SAS システム 18 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Normal Probability Plot 22.5+ * | * | ***+*+++++ | *******++ | +++******* | ************* |* * * ********** -12.5+++++++++ +----+----+----+----+----+----+----+----+----+----+ -2 -1 0 +1 +2
/* Lesson 12-5 */ /* File Name = les1205.sas 01/12/06 */ data gakusei; infile 'all05be.prn' firstobs=2; input sex $ shintyou taijyuu kyoui jitaku $ kodukai carryer $ tsuuwa; if sex^='M' & sex^='F' then delete; : 性別不明は除外 if shintyou=. | taijyuu=. | kyoui=. then delete; : 欠損のあるデータは除外 proc print data=gakusei(obs=10); run; proc corr data=gakusei; : 相関係数 where sex='M'; : 男性について run; : : proc reg data=gakusei; : 回帰分析 model taijyuu=shintyou kyoui; : where sex='M'; : 男性について output out=outreg1 predicted=pred1 residual=resid1; : run; : proc print data=outreg1(obs=15); run; proc plot data=outreg1; where sex='M'; : 対象データについて plot taijyuu*shintyou; plot taijyuu*kyoui; plot taijyuu*pred1; plot resid1*(pred1 shintyou kyoui taijyuu)/vref=0; : まとめて記述 /* plot resid1*pred1 /vref=0; plot resid1*shintyou/vref=0; plot resid1*kyoui /vref=0; plot resid1*taijyuu /vref=0; */ run; proc univariate data=outreg1 plot normal; var resid1; run;
SAS システム 2 17:36 Thursday, January 5, 2006 Correlation Analysis 5 'VAR' Variables: SHINTYOU TAIJYUU KYOUI KODUKAI TSUUWA Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum SHINTYOU 67 172.4 6.0708 11552.1 156.0 185.0 TAIJYUU 67 64.3985 9.0104 4314.7 46.0000 100.0 KYOUI 67 88.4925 8.4358 5929.0 56.0000 112.0 KODUKAI 63 52952.4 57161.2 3336000 0 300000 TSUUWA 11 7863.6 3899.3 86500.0 2500.0 15000.0 SAS システム 3 17:36 Thursday, January 5, 2006 Correlation Analysis Pearson Correlation Coefficients / Prob > |R| under Ho: Rho=0 / Number of Observations SHINTYOU TAIJYUU KYOUI KODUKAI TSUUWA SHINTYOU 1.00000 0.41210 0.18212 0.11812 0.15443 0.0 0.0005 0.1402 0.3565 0.6503 67 67 67 63 11 TAIJYUU 0.41210 1.00000 0.65267 -0.03516 0.35057 0.0005 0.0 0.0001 0.7844 0.2905 67 67 67 63 11 KYOUI 0.18212 0.65267 1.00000 -0.12039 -0.20651 0.1402 0.0001 0.0 0.3473 0.5424 67 67 67 63 11 KODUKAI 0.11812 -0.03516 -0.12039 1.00000 0.56460 0.3565 0.7844 0.3473 0.0 0.0704 63 63 63 63 11 TSUUWA 0.15443 0.35057 -0.20651 0.56460 1.00000 0.6503 0.2905 0.5424 0.0704 0.0 11 11 11 11 11 SAS システム 6 17:36 Thursday, January 5, 2006 Model: MODEL1 Dependent Variable: TAIJYUU Analysis of Variance Sum of Mean Source DF Squares Square F Value Prob>F Model 2 2759.15218 1379.57609 33.969 0.0001 Error 64 2599.21767 40.61278 C Total 66 5358.36985 Root MSE 6.37282 R-square 0.5149 Dep Mean 64.39851 Adj R-sq 0.4998 C.V. 9.89591 SAS システム 7 17:36 Thursday, January 5, 2006 Parameter Estimates Parameter Standard T for H0: Variable DF Estimate Error Parameter=0 Prob > |T| INTERCEP 1 -69.688001 22.69278666 -3.071 0.0031 SHINTYOU 1 0.450161 0.13141225 3.426 0.0011 KYOUI 1 0.638133 0.09457079 6.748 0.0001 SAS システム 10 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*SHINTYOU. 凡例: A = 1 OBS, B = 2 OBS, ... TAIJYUU | 100 + A | A A | 75 + A A A A A AA | B B A D A A A C A A D A A A | A A A A B A B A D B C A AAA A A A AA A 50 + A B A | | 25 + --+---------+---------+---------+---------+---------+---------+- 155 160 165 170 175 180 185 SHINTYOU SAS システム 11 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*KYOUI. 凡例: A = 1 OBS, B = 2 OBS, ... TAIJYUU | 100 + A | A A | 75 + AA BA A A | A A C BAI BAAB A | A A B C AAD EBF AA A 50 + A A A A | | 25 + ---+-------+-------+-------+-------+-------+-------+-------+-- 50 60 70 80 90 100 110 120 KYOUI SAS システム 12 17:36 Thursday, January 5, 2006 プロット : TAIJYUU*PRED1. 凡例: A = 1 OBS, B = 2 OBS, ... TAIJYUU | 100 + A | A A | 75 + B AAB A | BA A EABBBABB AAA | A AA A AABBABCECBAAA 50 + A A AA | | 25 + --+-----------+-----------+-----------+-----------+-----------+- 40 50 60 70 80 90 Predicted Value of TAIJYUU SAS システム 13 17:36 Thursday, January 5, 2006 プロット : RESID1*PRED1. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | i 20 + A A d | A A u | A A A BA A DAA AA a 0 +---------------A---A----A-BB-AADAABB--B-C----------A------------- l | AA A AABDBBAABB AA | -20 + ---+-----------+-----------+-----------+-----------+-----------+-- 40 50 60 70 80 90 Predicted Value of TAIJYUU SAS システム 14 17:36 Thursday, January 5, 2006 プロット : RESID1*SHINTYOU. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | i 20 + A A d | A A u | A B A C A B A B AA a 0 +----A-------A-----------A-B---A-C-A-A-A--AC---A-BA--B-A-A---A---- l | A B A A A B C A B A A A A BA A A | -20 + ---+---------+---------+---------+---------+---------+---------+-- 155 160 165 170 175 180 185 SHINTYOU SAS システム 15 17:36 Thursday, January 5, 2006 プロット : RESID1*KYOUI. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | i 20 + A A d | A A u | A A B A B BD B a 0 +-----------------------B-A-B---ABABAF-A-AC---A--------A---------- l | A B CBBAF AAB A A | -20 + -+--------+--------+--------+--------+--------+--------+--------+- 50 60 70 80 90 100 110 120 KYOUI SAS システム 16 17:36 Thursday, January 5, 2006 プロット : RESID1*TAIJYUU. 凡例: A = 1 OBS, B = 2 OBS, ... | R 40 + e | s | i 20 + A A d | A A u | A A A B AAAC A A AA a 0 +----------A-------A--ADACB-DA-A-CB------A------------------------ l | A A CAAB FABABA A | -20 + ---+---------+---------+---------+---------+---------+---------+-- 40 50 60 70 80 90 100 TAIJYUU SAS システム 17 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Moments N 67 Sum Wgts 67 Mean 0 Sum 0 Std Dev 6.275515 Variance 39.38209 Skewness 1.226471 Kurtosis 1.859485 USS 2599.218 CSS 2599.218 CV . Std Mean 0.766676 T:Mean=0 0 Pr>|T| 1.0000 Num ^= 0 67 Num > 0 26 M(Sign) -7.5 Pr>=|M| 0.0864 Sgn Rank -140 Pr>=|S| 0.3858 W:Normal 0.910467 PrSAS システム 20 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Stem Leaf # Boxplot 2 2 1 0 1 8 1 0 1 024 3 | 0 5555677778 10 | 0 00011233444 11 +--+--+ -0 44444333332221111111000 23 *-----* -0 998877766555555555 18 +-----+ ----+----+----+----+--- Multiply Stem.Leaf by 10**+1 SAS システム 21 17:36 Thursday, January 5, 2006 Univariate Procedure Variable=RESID1 Residual Normal Probability Plot 22.5+ * | * ++ | *+*+++++ 7.5+ +******* | +++****** | ************ -7.5+ * * * ********* +----+----+----+----+----+----+----+----+----+----+ -2 -1 0 +1 +2
where sex='M' and taijyuu<85;