
Java Programming (MindTap Course List)
8th Edition
ISBN: 9781285856919
Author: Joyce Farrell
Publisher: Cengage Learning
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Discrete Mathematics for Computer Engineering
this module is java 731 . make sure my answers are 1005 correct and the layout and structure is perfect and also include all comments etc. thank you
i have attached question 1 (40 marks) and question 2 (30 marks )
this is question 3:
Question3: (30 MARKS) Passenger Rail Agency for South Africa Train Scheduling System Problem Statement Design and implement a train scheduling system for Prasa railway network. The system should handle the following functionalities: 1. Scheduling trains: Allow the addition of train schedules, ensuring that no two trains use the same platform at the same time at any station. 2. Dynamic updates: Enable adding new train schedules and canceling existing ones. 3. Real-time simulation: Use multithreading to simulate the operation of trains (e.g., arriving, departing). 4. Data management: Use ArrayList to manage train schedules and…
this module is java 731 . make sure my answers are 1005 correct and the layout and structure is perfect and also include all comments etc. thank you
i have attached question 1 (40 marks) and question 2 (30 marks )
this is question 3:
Question3: (30 MARKS) Passenger Rail Agency for South Africa Train Scheduling System Problem Statement Design and implement a train scheduling system for Prasa railway network. The system should handle the following functionalities: 1. Scheduling trains: Allow the addition of train schedules, ensuring that no two trains use the same platform at the same time at any station. 2. Dynamic updates: Enable adding new train schedules and canceling existing ones. 3. Real-time simulation: Use multithreading to simulate the operation of trains (e.g., arriving, departing). 4. Data management: Use ArrayList to manage train schedules and…
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- here is example 7.6## Example 7.6 Suppose the sample population is χ 2 (2), which is non-normal but with same variance 4. ▶ Repeat the simulation, but replacing the N(0, 4) samples with χ 2 (2) samples. ▶ Calculate the empirical confidence level.(Empirical confidence level) n <- 20 alpha <- 0.05 UCL <- replicate(1000, expr = { x <- rchisq(n,df=2) (n-1)*var(x)/qchisq(alpha,df=n-1) }) sum(UCL >4) mean(UCL > 4) ## t.test function n <- 20 x <- rnorm(n,mean=2) result <- t.test(x,mu=1) result$statistic result$parameter result$p.value result$conf.int result$estimatearrow_forwardusing r languagearrow_forwardusing r languagearrow_forward
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