Experimental Design in Agriculture Name: CROP 590 First Midterm Winter 2016 Please show your work! 1a) In just a few sentences, describe the objectives of a planned experiment that you have encountered in your field of study. 6 pts 1b) Using your example, define the following: 8 pts The treatments The experimental units Blocking factors (if any), and explain the reason that they are used (or not used) 1c) 9 pts Continuing with your example, describe three specific things that the researcher could do to reduce the chances of making a Type II error. 1 2) A plant breeder in Zambia would like to compare three varieties of maize for grain yield: a hybrid, and open-pollinated variety (OPV) and a local (landrace) variety. The experiment is conducted as a Completely Randomized Design with 4 replications. The mean grain yields for the varieties in Mg/ha are as follows: Varieties Means Hybrid OPV Local 3.35 2.90 2.15 a) Calculate the Sum of Squares for Treatments: 8 pts b) If the LSD (=0.05) value is 0.55 for this experiment, then the hybrid is significantly different from the OPV (circle the correct answer). 4 pts TRUE FALSE 3) Discuss the potential advantages of using long, narrow plots in field experiments. Describe at least one scenario where another plot shape might be preferred. 4) When there are missing plots in a Randomized Complete Block Design (choose one answer): 9 pts 5 pts a) A degree of freedom must be subtracted from the Error df for each missing plot b) We should not rely on the Analysis Tool Pak in Excel to perform the ANOVA c) Adjusted means in SAS (lsmeans) may be different than the arithmetic means d) All of the above 2 5) An animal scientist wished to test the effects of 5 different feeding regimens on the weight gain of pigs. Each treatment was randomly assigned to five pigs. a) Fill in the boxes to complete the ANOVA. 14 pts Source DF SS Total 24 1081 Feeding Regimens 6 pts MS F 68 b) Do the results indicate that there were differences among the feeding regimens at the = 0.05 probability level? What is your proof? (Use the tables at the back of this exam) 6 pts 8 pts c) The grand mean for the experiment was 55 pounds. What was the Coefficient of Variation (CV%)? d) Regimen #1 has a mean of 60 pounds. Calculate the upper and lower limits for a 95% confidence around this mean. (Use the tables at the back of this exam) 3 6) The response of soybeans to four seed treatments was measured in a Randomized Complete Block Design. The output of the analysis from SAS PROC GLM is shown below. Dependent Variable: response Source DF Sum of Squares Mean Square F Value Pr > F Model 8 878.0000000 109.7500000 Error 15 83.9583333 5.5972222 Corrected Total 23 961.9583333 19.61 <.0001 R-Square Coeff Var Root MSE response Mean 0.912721 Source 14.08940 2.365845 16.79167 DF Type III SS Mean Square F Value Pr > F block 5 435.2083333 87.0416667 15.55 <.0001 treatment 3 442.7916667 147.5972222 26.37 <.0001 a) Do the results indicate that there were differences among the treatments? Support your statement with evidence from the output above. 5 pts b) Calculate the standard error of a difference between treatment means for this experiment. 6 pts 6 pts c) The relative efficiency for this experiment compared to a CRD is 4.16. Circle the correct statement below: i. The value of 4.16 > 1, so a CRD would have been more efficient than the RBD ii. Blocking increased efficiency compared to a CRD by 416% iii. 25 replications in a CRD would be needed to obtain the same level of efficiency as the RBD. iv. None of the above 4 F Distribution 5% Points Denominator Student's t Distribution Numerator (2-tailed probability) df 1 2 3 4 5 6 7 1 161.45 199.50 215.71 224.58 230.16 233.99 236.77 2 18.51 19.00 19.16 19.25 19.30 19.33 19.35 3 10.13 9.55 9.28 9.12 9.01 8.94 8.89 4 7.71 6.94 6.59 6.39 6.26 6.16 6.09 5 6.61 5.79 5.41 5.19 5.05 4.95 4.88 6 5.99 5.14 4.76 4.53 4.39 4.28 4.21 7 5.59 4.74 4.35 4.12 3.97 3.87 3.79 8 5.32 4.46 4.07 3.84 3.69 3.58 3.50 9 5.12 4.26 3.86 3.63 3.48 3.37 3.29 10 4.96 4.10 3.71 3.48 3.33 3.22 3.14 11 4.84 3.98 3.59 3.36 3.20 3.09 3.01 12 4.75 3.89 3.49 3.26 3.11 3.00 2.91 13 4.67 3.81 3.41 3.18 3.03 2.92 2.83 14 4.60 3.74 3.34 3.11 2.96 2.85 2.76 15 4.54 3.68 3.29 3.06 2.90 2.79 2.71 16 4.49 3.63 3.24 3.01 2.85 2.74 2.66 17 4.45 3.59 3.20 2.96 2.81 2.70 2.61 18 4.41 3.55 3.16 2.93 2.77 2.66 2.58 19 4.38 3.52 3.13 2.90 2.74 2.63 2.54 20 4.35 3.49 3.10 2.87 2.71 2.60 2.51 21 4.32 3.47 3.07 2.84 2.68 2.57 2.49 22 4.30 3.44 3.05 2.82 2.66 2.55 2.46 23 4.28 3.42 3.03 2.80 2.64 2.53 2.44 24 4.26 3.40 3.01 2.78 2.62 2.51 2.42 25 4.24 3.39 2.99 2.76 2.60 2.49 2.40 26 4.23 3.37 2.98 2.74 2.59 2.47 2.39 27 4.21 3.35 2.96 2.73 2.57 2.46 2.37 28 4.20 3.34 2.95 2.71 2.56 2.45 2.36 29 4.18 3.33 2.93 2.70 2.55 2.43 2.35 30 4.17 3.32 2.92 2.69 2.53 2.42 2.33 5 df 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 0.4 1.376 1.061 0.978 0.941 0.920 0.906 0.896 0.889 0.883 0.879 0.876 0.873 0.870 0.868 0.866 0.865 0.863 0.862 0.861 0.860 0.859 0.858 0.858 0.857 0.856 0.856 0.855 0.855 0.854 0.854 0.2 0.05 3.078 12.706 1.886 4.303 1.638 3.182 1.533 2.776 1.476 2.571 1.440 2.447 1.415 2.365 1.397 2.306 1.383 2.262 1.372 2.228 1.363 2.201 1.356 2.179 1.350 2.160 1.345 2.145 1.341 2.131 1.337 2.120 1.333 2.110 1.330 2.101 1.328 2.093 1.325 2.086 1.323 2.080 1.321 2.074 1.319 2.069 1.318 2.064 1.316 2.060 1.315 2.056 1.314 2.052 1.313 2.048 1.311 2.045 1.310 2.042