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Current File : /usr/lib/python3/dist-packages/scipy/stats/tests/data/nist_anova/SmLs09.dat
NIST/ITL StRD 
Dataset Name:   SmLs09   (SmLs09.dat)


File Format:    ASCII
                Certified Values   (lines 41 to 47)
                Data               (lines 61 to 18069) 


Procedure:      Analysis of Variance


Reference:      Simon, Stephen D. and Lesage, James P. (1989).
                "Assessing the Accuracy of ANOVA Calculations in
                Statistical Software".
                Computational Statistics & Data Analysis, 8, pp. 325-332.


Data:           1 Factor
                9 Treatments
                2001 Replicates/Cell
                18009 Observations
                13 Constant Leading Digits
                Higher Level of Difficulty
                Generated Data


Model:          10 Parameters (mu,tau_1, ... , tau_9)
                y_{ij} = mu + tau_i + epsilon_{ij}






Certified Values:

Source of                  Sums of               Mean               
Variation          df      Squares              Squares              F Statistic

Between Treatment     8 1.60080000000000E+02 2.00100000000000E+01 2.00100000000000E+03
Within Treatment  18000 1.80000000000000E+02 1.00000000000000E-02

                  Certified R-Squared 4.70712773465067E-01

                  Certified Residual
                  Standard Deviation  1.00000000000000E-01












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           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6
           9    1000000000000.4
           9    1000000000000.6

Youez - 2016 - github.com/yon3zu
LinuXploit