tailieunhanh - Engineering Statistics Handbook Episode 9 Part 4

Tham khảo tài liệu 'engineering statistics handbook episode 9 part 4', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | . Background and Data http div898 handbook pmc section6 13 of 14 5 1 2006 10 35 55 AM . Background and Data NIST SEMATECH HOME tools RAIDS search SACK NEXT http div898 handbook pmc section6 14 of 14 5 1 2006 10 35 55 AM . Model Identification Interpretation of the Run Sequence Plot We can make the following conclusions from the run sequence plot. 1. The data show strong and positive autocorrelation. 2. There does not seem to be a significant trend or any obvious seasonal pattern in the data. The next step is to examine the sample autocorrelations using the autocorrelation plot. Autocorrelation Plot Interpretation of the Autocorrelation Plot The autocorrelation plot has a 95 confidence band which is constructed based on the assumption that the process is a moving average process. The autocorrelation plot shows that the sample autocorrelations are very strong and positive and decay very slowly. The autocorrelation plot indicates that the process is non-stationary and suggests an ARIMA model. The next step is to difference the data. http div898 handbook pmc section6 2 of 5 5 1 2006 10 35 56 AM