A computer manufacturer is interested in comparing assembly times for two keyboard assembly processes. Assembly times can vary considerably from worker to worker, and the company decides to eliminate this effect by selecting 12 workers at random and timing each worker on each assembly process. Half of the workers are chosen at random to use Process 1 first, and the rest use Process 2 first. For each worker and each process, the assembly time (in minutes) is recorded, as shown in the table below. Worker Process 1 Process 2 Difference (Process 1 - Process 2) Send data to calculator 1 43 2 83 35 78 8 5 3 74 66 4 51 30 5 60 47 6 7 8 9 10 11 12 75 76 (a) state the null hypothesis Ho and the alternative hypothesis H₁. Ho :O H₁ :0 (b) Determine the type of test statistic to use. Type of test statistic: (Choose one) 48 81 61 61 8 21 13 -1 -13 20 88 (c) Find the value of the test statistic. (Round to three or more decimal places.) 0 93 44 41 49 54 Based on these data, can the company conclude, at the 0.05 level of significance, that the mean assembly times for the two processes differ? Answer this question by performing a hypothesis test regarding (which is μ with a letter "d" subscript), the population mean difference in assembly times for the two processes. Assume that this population of differences (Process 1 minus Process 2) is normally distributed. (e) At the 0.05 level, can the company conclude that the mean assembly times for the two processes differ? OYes O No 32 -5 3 17 -9 Perform a two-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places and round your answers as specified. (If necessary, consult a list of formulas.) (d) Find the two critical values at the 0.05 level of significance. (Round to three or more decimal places.) and 63 H X S Do X Р 0 5

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