Than all the oca cultivars but the 5 ocas means could

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than all the oca cultivars, but the 5 ocas’ means could all be the same. (b) From the residual vs. fitted values plot, we see that the rhubard residuals are way larger than the oca residuals. It is also suggested by the large SD in the rhubarb sample (785), about 10 times bigger than those in the oca sam- ples (41-72). The large rhubarb residuals appear as large outliers (positive and negative) in the normal scores plot. That’s what makes plot unusual. Independence assumption: not met. Duplicate values are ’nested’ within tubers or stalks. There are really only 4 independent tubers and 4 independent stalks. But all 8 ob- servations within each sample are not all independent. Equal variances: not met, as said earlier. Normality: may be. Even though the normal scores plot is not linear, its shape might be only explained by the rhubarb’s large SD. (c) dfCultivar is 5 - 1 = 4 and dfError is 35 so the p-value is < . 001. Strong evidence that the 5 oca cultivars do not all have the same mean oxalate content. (d) For α = 0 . 01 we get Q = 5 . 05 at df=30 and 4.93 at df=40. Our dfError=35. We prefer being conservative and use Q = 5 . 0, close to the Q value at df=30.(The true value is Q = 4 . 98 at dfError= 35). The critical distance is the d Q = 5 . 0 3251 * 1 / 8 = 100 . 8. Only cultivar O2 is signifi- cantly different from all other oca cultivars. O1 O4 O3 O5 O2 306 336 397 403 539 --------------- 5. (a) False. The equality is always valid, even when X and Y are dependent. (b) True. The median depends on middle values only, not on the largest or on the lowest values. The mean depends on all values and can be pulled by outliers. (c) False. The t-distribution is symmetric, the F-distribution is not. (d) False. The Binomial can be skewed, but never bimodal. (e) True. The t-test depends on means, which are affected by outliers. The Mann-Whitney test depends on ranks only, not affected by extreme values. 1
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