Questions We wish to compare two queuing disciplines for CPU service (say CPU-A discipline and CPU-B discipline) propose

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Questions
We wish to compare two queuing disciplines for CPU service (sayCPU-A discipline and CPU-B discipline) proposed by the designers ofthe operating system. To do this, we place test machines into twosettings considered to be uniform in terms of the rate and durationof arriving jobs and measure the waiting time (in seconds). We willget a random sample of size 30 of X data (CPU-A) and a randomsample of size 30 of Y data (CPU-B).
1. Obtain the X data. In reality you would perform theexperiment, measure and record the results of 30 waiting times. Wewill “save time” and simulate our own data from a normaldistribution. Generate 30 random observations x1, x2,…, x30 from aN(80, 1 2 ) distribution (i.e. from a normal distribution withmean=80 and standard deviation=1). These will be the CPU-A data.Screenshot the dialogue box (with information filled) which youused to generate the random observations and paste it onto yourMicrosoft Word file. Also, copy and paste the CPU-A data x1, x2,…,x30 onto the same Microsoft Word file. {Hint: click on Data\DataAnalysis\Random Number Generation. In the Random Number GenerationDialogue Box, leave the Random Seed empty} (2 marks)
2. Obtain the Y data. Generate 30 random observations y1,y2,…,y30 from a N(81, 1.52 ) distribution (i.e. from a normaldistribution with mean=81 and standard deviation=1.5). . These willbe the CPU-B data. Screenshot the dialogue box (with informationfilled) which you used to generate the random observations andpaste it onto your Microsoft Word file. Also, copy and paste theCPU-B data y1, y2,…,y30 onto the same Microsoft Word file. {Hint:click on Data\Data Analysis\Random Number Generation. In the RandomNumber Generation Dialogue Box, leave the Random Seed empty}
3. We also must pretend that we do not know the truedistributions which generated the simulated data. Therefore, forgetthat the N(80, 1 2 ) and N(81, 1.52 ) ever existed, and concentrateon the data that you have in hand. Generate software output whichshows (and copy or screenshot the relevant output from MicrosoftExcel to Microsoft Word file and indicate on the output todemonstrate where it shows):
(a) 𝑋̅ and 𝑌̅; standard deviation of X and Y; median of X and Y.(3 marks) (b) Group the CPU-A data x1, x2,…, x30 by showing the BinRange & Frequency Output clearly and fill up the frequency inthe table below: Waiting Time (seconds) Frequency ≤77 77-78 78-7979-80 80-81 81-82 82-83 >83 (Note: Depending on your data, it islikely that you obtain zero or very low frequency for the firstclass and the last class) Plot the histogram of CPU-A data andcomment. (9 marks)
(c) Test, at 5% level of significance, whether the mean waitingtime of CPU-A is different from 80.3 seconds. State the null andalternative hypothesis, p-value and conclusion clearly. (7marks)
(d) The designers claim that the mean waiting time resultingfrom the CPU-B discipline is higher than that of CPU-A discipline.Assuming that the variances of waiting time of CPU-A and CPU-B areunequal, test, at 5% level of significance, whether the claim isvalidated. State the null and alternative hypothesis, p-value andconclusion clearly. (7 marks)