The comp wise p val is 002 p 01 using bonferroni with

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The comp-wise p-val is: . 002 < p < . 01 . Using Bonferroni with 2 contrasts (it is the number of contrasts, not the number of treat- ments that is important!!!), the comp-wise p- val needs to be doubled. Thus . 004 < p < . 02 which is less than .05; thus, there is solid ev- idence against the equality of A and the av- erage of the new formulation treatments. For (ii), t=33.55/48.76=0.69. Using Bonferroni, p > . 40 and there is no meaningful evidence against the null of no linear trend for additive. 2. (a) ˆ b 1 = 22 . 93 / 196 . 90 = . 116 . This means that for each increase in temperature of one degree C, the rate of oxygen consumption decreases by .116 ml/g/hr. (b) SSReg = ˆ b 1 ( 22 . 93) = 2 . 67 . Thus, the ANOVA table for regression can be written: source df SS MS regr 1 2.67 2.67 error 8 .41 .051 total 9 3.08 —— The stated test is H 0 : b 1 = 0 vs H A : b 1 negationslash = 0. F=2.67/.051= 52.1 on (1,8) df. Thus, p < . 001 and the rate de- pends strongly on the temperature. (c) Here we focus on ˆ Y as an estimator. se ( ˆ Y e ) = s p (1 /n ) + (5 ¯ x ) 2 / ( P ( x i ¯ x ) 2 ) = . 079. Now, t 8 ,. 025 = 2 . 306 and ˆ Y = 3 . 326. Thus, a 95% confidence interval for ˆ Y e is (3.144, 3.508). Thus, at 95 % confidence, a plausible range for the mean rate of oxygen consumption is from 3.144 to 3.508 ml/g/hr. Since the value of “3”
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