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Engineering Statistics Handbook Episode 5 Part 4

Tham khảo tài liệu 'engineering statistics handbook episode 5 part 4', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 3.5.2.2. Box Plots by Factors Conclusion From Box Plot We can draw the following conclusion from this box plot. Although there are some minor differences in location and spread between the samples these differences do not show a noticeable pattern and do not seem significant. NIST SEMATECH HOME TOOLS it AIDS SEARCH SACK NEXT http www.itl.nist.gov div898 handbook ppc section5 ppc522.htm 4 of 4 5 1 2006 10 18 12 AM 3.5.2.3. Analysis of Variance 1.2478 73.441 FACTOR 4 9 0.5205 14.172 0.000009 0.000001 RESIDUAL 165 0.000312 0.000002 RESIDUAL STANDARD DEVIATION 0.00137439766 RESIDUAL DEGREES OF FREEDOM 165 ESTIMATION GRAND MEAN 0.12395893037E 00 GRAND STANDARD DEVIATION 0.15631503193E-02 SD EFFECT LEVEL-ID NI MEAN EFFECT FACTOR 1-- 1.00000 60. 0.12489 0.00093 0.00014 2.00000 60. 0.12297 -0.00099 0.00014 3.00000 60. 0.12402 0.00006 0.00014 FACTOR 2-- 1.00000 60. 0.12409 0.00013 0.00014 2.00000 60. 0.12403 0.00007 0.00014 3.00000 60. 0.12376 -0.00020 0.00014 FACTOR 3-- 1.00000 90. 0.12384 -0.00011 0.00010 2.00000 90. 0.12407 0.00011 0.00010 FACTOR 4-- 1.00000 18. 0.12371 -0.00025 0.00031 2.00000 18. 0.12405 0.00009 0.00031 3.00000 18. 0.12398 0.00002 0.00031 4.00000 18. 0.12382 -0.00014 0.00031 5.00000 18. 0.12426 0.00030 0.00031 6.00000 18. 0.12379 -0.00016 0.00031 7.00000 18. 0.12406 0.00010 0.00031 8.00000 18. 0.12376 -0.00020 http www.itl.nist.gov div898 handbook ppc section5 ppc523.htm 2 of 6 5 1 2006 10 18 12 AM 0.00031 9.00000 18 . 0.12376 -0.00020 0.00031 0.00031 10.00000 18 . 0.12440 0.00044 MODEL RESIDUAL STANDARD DEVIATION CONSTANT ONLY-- 0.0015631503 CONSTANT FACTOR 1 ONLY-- CONSTANT FACTOR 2 ONLY-- CONSTANT FACTOR 3 ONLY-- CONSTANT FACTOR 4 ONLY-- CONSTANT ALL 4 FACTORS -- 0.0013584237 0.0015652323 0.0015633047 0.0015876852 0.0013743977 Interpretation The first thing to note is that Dataplot fits an overall mean when ofANOVA performing the ANOVA. That is it fits the model .