CROP 590 Experimental Design in Agriculture Lab exercise – Week 10 Special Topic: Matrix Algebra ANOVA and Regression in Matrix Notation Refer to the power point presentation for background information for this exercise. 6 4 A 8 2 3 9 2 7 2 1 B 6 8 3 7 5 4 1) What is b3,2? What are the dimensions of B? b3,2 = 5 B is a 4 x 2 matrix 2) Calculate C = A – B 3) Calculate E = A + B 4 0 3 2 C 2 3 6 3 8 6 5 16 E 14 7 10 11 4) What is the transpose of A? 5) Calculate A’B 6 4 8 2 A 3 9 2 7 2 6 4 8 2 1 AB 3 9 2 7 6 8 1 3 7 80 5 83 4 94 110 6) Calculate the determinant of H and the inverse of H. 7 2 H |H| = ab-cd = 7*3-2*5 = 21 – 10 = 11 5 3 3 2 11 0.2727 0.1818 1 H 5 117 11 11 0.4545 0.6364 7) What is the trace of H? tr(H) = 7 + 3 = 10 8) You wish to fit a quadratic curve to the following data. X 2 4 6 8 Y 6 13 17 16 Yi = b0 + b1Xi + b2Xi2 In Matrix notation , Y = XB + e Y = 6 13 17 16 X 1 1 1 1 B + e 4 e1 b 0 16 e 2 b1 36 e3 b2 64 e 4 2 4 6 8 The solution to the normal equations is B = X’X-1X’Y 9) Use matrix functions in Excel to solve for B (MMULT, TRANSPOSE, and MINVERSE) 10) Solve for B using PROC IML in SAS PROC IML; X={1 2 4, 1 4 16, 1 6 36, 1 8 64}; Y={6, 13, 17, 16}; XPX=X`*X; print XPX; XPXinv=inv(XPX); print XPXinv; XPY=X`*Y; print XPY; B=XPXinv*XPY; print B; quit ; Yi = -5.5 + 6.7Xi -0.5Xi 2 2 11) Now let’s analyze a simple CRD experiment with matrix notation: Y = X 3 1 4 1 1 1 4 1 8 1 6 1 1 1 0 0 0 0 B + e 0 e11 e 0 b0 12 1 e 21 b1 1 e 22 b2 e31 0 0 e32 proc iml; X={1 1 0, 1 1 0, 1 0 1, 1 0 1, 1 0 0, 1 0 0} ; Y={3, 4, 1, 4, 8, 6}; CF=sum(Y)*sum(Y)/countn(Y); XPX=X`*X; XPXinv=inv(XPX); XPY=X`*Y; B=XPXinv*XPY; SSTotal=(Y`*Y)-CF; SSTrt=B`*XPY-CF; SSE=SSTotal-SSTrt; YHAT=X*B; Resid=Y-YHAT; print SSTotal SSTrt SSE B YHAT Resid; QUIT; Refer to the power point presentation for more details…. 3