1. The problem statement, all variables and given/known data The article “Variance Reduction Techniques: Experimental Comparison and Analysis for Single Systems” (I.Sabuncuoglu,M. Fadiloglu, and S. Celik, IIE Transactions, 2008:538–551) describes a study of the effectiveness of the method of Latin Hypercube Sampling in reducing the variance of estimators of the mean time-in-system for queueing models. For the M/M/1 queueing model, ten replications of the experiment yielded an average reduction of 6.1 with a standard deviation of 4.1. For the serial line model, ten replications yielded anaveragereductionof6.6withastandarddeviationof 4.3. Can you conclude that the mean reductions differ between the two models? 2. Relevant equations nx = 10 ; X= 6.1 ; Sx = 4.1 ny = 10 ; Y= 6.6 ; Sy = 4.3 H0: X-Y = 0 ; H1: X-Y ≠0 ; Δ0 = 0 As we cannot assume standard deviations to be equal, we use the formula that find student's t and the degree of freedom v. 3. The attempt at a solution It is found that v = 17.959, rounded down to 17 with t calculated as 0.2661 As H1: X-Y ≠0, P is the sum of cutoffs We are to find Alpha, based on v = 17 and t' = 2t = 0.5322 It is founded that alpha between 0.25 and 0.40 All of which higher than 5%, so H0 is not rejected, and cannot conclude the mean reductions differ between the two models. My approaches correct, as well as the answer make sense? Thanks!