Hello,

Please help me (I really need help with this problem) write program in SAS for task # 1 and most importantly, conduct a full analysis of the results, including testing the hypothesis, F-values ??and other things, problem required a full analysis of the results.

Problem #1: RCBD with subsampling Five evaluators (A, B, C, D, E) rated four treatment methods (1, 2, 3, 4) on a scale of seven. For each evaluator, one sample of each treatment method was prepared, which was randomly distributed between them, distributed samples were evaluated twice. In other words, one evaluator rated each of 4 treatments twice, completing in total 8 evaluations. Then, the evaluators are considering in the form of a block [Table 1]. Evaluators T1 T2 T3 T4 A 4, 2 2, 2 2, 3 3, 3 B 3, 4 2, 3 4, 3 1, 1 C 3, 5 3, 2 3, 3 2, 2 4, 3 4, 1 2, 4 1, 1 E 3, 3 3, 2 1, 2 2, 1ANOVA Table SOV Df F Rep r-1 Rep MS/Pooled Error MS Trt t-1 Trt MS/Pooled Error MS Experimental Error (r-1)(t-1) Sampling Error (rts-1)-(tr-1) Total trs-1 Pooled Error MS Exp Error df + Sampling Error df Example Treatment Rep Sample A B C 78 68 89 82 64 87 Y11.=160 Y21.=132 Y31.=176 Y.1.=468 N - 74 62 88 78 66 92 Y 12.=152 Y 22.= 128 Y32.=180 Y.2.=460 3 80 70 90 84 60 96 Y 13.=164 Y 23.=130 Y 33.=186 Y.3.=480 Yi 476 390 542 Y..= 1408 Step 1. Calculate the Correction Factor (CF). Y2 14082 rts 3(3) (2) - =110,136.889 Step 2. Calculate the Total SS: Total SS = _Ya - CF = (782 +822 +74" +...+96?)-CF = 2121.111 Step 3. Calculate the Replicate SS. Rep SS = > 4682 4602 4802 3(2) 3 (2 ) 3 ( 2 ) -CF = 33.778 Step 4. Calculate the Treatment SS: Treatment SS = Z -CF 4762 3902 542 -CF 3 ( 2 ) 3 ( 2 ) 3 ( 2 ) = 1936.444Step 5. Calculate the SS Among Experimental Units Total (SSAEUT) SS AEUT = >- -CF 1602 1522 1642 2 -+...+186' 2 -CF = 2003.111 Step 6. Calculate the Experimental Error SS: Experimental Error SS = SAEUT - SS TRT - SS REP = 2003.111 - 1936.444 - 33.778 = 32.889 Step 7. Calculate the Sampling Error SS: Sampling Error SS = Total SS - SSAEUT = 2121.111 -2003.111 = 118.0 Step 8. Complete the ANOVA Table: SOV Df SS MS F Rep r-1=2 33.778 16.889 2.054ns Trt t-1 = 2 1936.444 968.222 117.76" Experimental Error (r-1)(t-1) = 4 32.889 8.222 Sampling Error (trs-1) - (tr-1) = 9 118.0 13.111 Total trs-1 = 17 2121.111 Step 9. Test the homogeneity of variance between the Experimental and Sampling Error MS using the Folded F-test. Step 9.1 Calculate the F-value using the Folded F-test Folded F = Sampling Error MS / Experimental Error MS F = 8.222 13.111 = 0.627 Step 9.2 Look up the table F-value This F-test is a one-tail test because there is the expectation that the Experimental Error MS (63 + 50 ) is going to be larger than the Sampling Error MS (6; ) . Thus, if you are testing o = 0.01, then you need to use the F-table for a = 0.01 (Appendix Table IV, page 612). F 0.01,(ExpiErraf )(SampErraf) =0.01:4.9 = 6.42 Step 9.3 Make conclusions: Since the calculated value of F (0.627) is less than the Table-F value (6.42), we fail to reject Ho: Sampling Error MS = Experimental Error MS at the 99% level of confidence. Therefore, we can calculate a Pooled Error MS Step 10: Calculate the Pooled Error df and the Pooled Error MS Pooled Error df = Sampling Error df + Experimental Error df = (9+4) = 13 Pooled Error MS = Sampling Error SS + Experimental Error SS Sampling Error df + Experimental Error df 118.0+32.889 4+9 =11.607Step 11: Complete the ANOVA using the Pooled Error MS as the denominator of the F- test SOV Df SS MS F Rep r-1=2 33.778 16.889 1.455ns Trt t-1 = 2 1936.444 968.222 83.42"* Experimental Error (r-1)(t-1) = 4 32.889 8.222 Sampling Error (trs-1) - (tr-1) = 9 118.0 13.111 Total trs-1 = 17 2121.111 Pooled Error Expt Error df + Samp Error df=13 150.889 11.607 Step 12. Calculate LSD. LSD TRT = .05/ 2 PooledErrorMS rs = 2.16 2(11.607) 3*2 = 4.24 Step 13. Compare treatment means Treatment Mean B 65.0a A 79.3 b 90.3 c 6/13 SAS for the RCBD with Sampling Commands options pageno=1; data rcbdsamp; input TRT $ Rep Sample Yield; datalines ; A : : n n n nnnwwww ww > > > > > WWNN - - WWNN - - WWNN - N - N - N - N - N - N - N - N - N - 78 82 74 78 80 84 68 64 62 66 70 60 89 87 88 92 90 96 proc anova; class rep trt; model yield=rep trt rep*trt; *comment rep*trt is the experimental error ; test h=rep trt e=rep*trt; means trt/1sd e=rep*trt; title 'RCBD with Sampling - Using the Experimental Error as the Denominator of the F-test' ; run; proc anova; class rep trt; model yield=rep trt; *comment by leaving out the rep*trt term, you are allowing SAS to calculate the pooled error ; means trt/1sd; title 'RCBD with Sampling - Using the Pooled Error as the Denominator of the F-test' ; run