tions. (h) false: The SE goes down to 0, but theSD stays about the same.4.(a) A paired t-test: the same authors are used in eachof the two samples.(b) Assumptions are:linearity of the relationship,and equal variance. The linearity assumption isclearly 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 thevariability of the points around thecurveseemsto be quite homogeneous.(c) i.An independent sample t-test (forcing or notforcing equal variances, it shouldn’t matter).ii.Try to transform the data and use a t-teston the transformed data, if a transformation canbe 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 forceequal variances. Use the Mann-Whitney test if notransformation can make both samples look nor-mally distributed.iii.Use a t-test.The rather large sample sizemakes it okay even if the data are not normallydistributed.5(a)¯KMN+¯KS2= 2.4, then 2.40-¯KW1 = 0.165.The standard error for this contrast is√.567*115+415+415=.2381. We get a t-value oft=0.1650.2381=.693 on df= 126.Using 100 df in thetable, we get that the p-value is> .20 so we failto reject the null hypothesis that the true averagepulse rate of crickets at KW1 is equal to the mean
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