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Engineering Statistics Handbook Episode 2 Part 11

Tham khảo tài liệu 'engineering statistics handbook episode 2 part 11', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | I.4.2.3.2. Test Underlying Assumptions Spectral Plot Another useful plot for non-random data is the spectral plot. Quantitative Output Summary Statistics This spectral plot shows a single dominant low frequency peak. Although the 4-plot above clearly shows the violation of the assumptions we supplement the graphical output with some quantitative measures. As a first step in the analysis a table of summary statistics is computed from the data. The following table generated by Dataplot shows a typical set of statistics. SUMMARY NUMBER OF OBSERVATIONS 500 LOCATION MEASURES DISPERSION MEASURES MIDRANGE 0.2888407E 01 RANGE 0.9053595E 01 MEAN 0.3216681E 01 STAND . DEV. 0.2078675E 01 MIDMEAN 0.4791331E 01 AV. AB. DEV. 0.1660585E 01 MEDIAN 0.3612030E 01 MINIMUM -0.1638390E 01 LOWER QUART. 0.1747245E 01 LOWER HINGE 0.1741042E 01 UPPER HINGE 0.4682273E 01 UPPER QUART. 0.4681717E 01 http www.itl.nist.gov div898 handbook eda section4 eda4232.htm 3 of 7 5 1 2006 9 58 36 AM I.4.2.3.2. Test Underlying Assumptions MAXIMUM 0.7415205E 01 RANDOMNESS MEASURES DISTRIBUTIONAL MEASURES AUTOCO COEF 0.9868608E 00 ST. 3RD MOM. -0.4448926E 00 0.0000000E 00 ST. 4TH MOM. 0.2397789E 01 0.0000000E 00 ST. WILK-SHA -0.1279870E 02 UNIFORM PPCC 0.9765666E 00 NORMAL PPCC 0.9811183E 00 TUK -.5 PPCC 0.7754489E 00 CAUCHY PPCC 0.4165502E 00 The value of the autocorrelation statistic 0.987 is evidence of a very strong autocorrelation. Location One way to quantify a change in location over time is to fit a straight line to the data set using the index variable X 1 2 . N with N denoting the number of observations. If there is no significant drift in the location the slope parameter should be zero. For this data set Dataplot generates the following output LEAST SQUARES MULTILINEAR FIT sAmple size N 500 NUMBER OF VARIABLES 1 NO REPLICATION CASE PARAMETER ESTIMATES APPROX. ST. DEV. T VALUE 1 A0 1.83351 0.1721 10.65 2 A1 X 0.552164E-02 0.5953E-03 9.275 RESIDUAL STANDARD DEVIATION 1.921416 RESIDUAL DEGREES OF .