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# H false the se goes down to 0 but the sd stays about

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tions. (h) false: The SE goes down to 0, but the SD stays about the same. 4.(a) A paired t-test: the same authors are used in each of the two samples. (b) Assumptions are: linearity of the relationship, and equal variance. The linearity assumption is clearly violated: there appears to be a curved re- lationship. In light of this, looking at the homoge- neous assumption is a little bit irrelevant. But the variability of the points around the curve seems to be quite homogeneous. (c) i. An independent sample t-test (forcing or not forcing equal variances, it shouldn’t matter). ii. Try to transform the data and use a t-test on the transformed data, if a transformation can be found to make the samples look normally dis- tributed. If the transformed data have very dif- ferent variances, use the t-test that does not force equal variances. Use the Mann-Whitney test if no transformation can make both samples look nor- mally distributed. iii. Use a t-test. The rather large sample size makes it okay even if the data are not normally distributed. 5(a) ¯ KMN + ¯ KS 2 = 2 . 4, then 2 . 40 - ¯ KW1 = 0 . 165. The standard error for this contrast is . 567 * 1 15 + 4 15 + 4 15 = . 2381. We get a t-value of t = 0 . 165 0 . 2381 = . 693 on df= 126. Using 100 df in the table, we get that the p-value is > . 20 so we fail to reject the null hypothesis that the true average pulse rate of crickets at KW1 is equal to the mean
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