/* NIST/ITL StRD ANOVA Difficulty=Lower n_i=5 k=5 Observed Dataset Name: Si_Resistivity (Si_Resistivity.dat) Procedure: Analysis of Variance Reference: Ehrstein, James and Croarkin, M. Carroll. Unpublished NIST dataset. Data: 1 Factor 5 Treatments 5 Replicates/Cell 25 Observations 3 Constant Leading Digits Lower Level of Difficulty Observed Data Model: 6 Parameters (mu,tau_1, ... , tau_5) y_{ij} = mu + tau_i + epsilon_{ij} Certified Values: Source of Sums of Mean Variation df Squares Squares F Statistic Between Instrument 4 5.11462616000000E-02 1.27865654000000E-02 1.18046237440255E+00 Within Instrument 20 2.16636560000000E-01 1.08318280000000E-02 Certified R-Squared 1.90999039051129E-01 Certified Residual Standard Deviation 1.04076068334656E-01 */ clear scalar N = 25 scalar df_r = 20 scalar df_m = 4 scalar mss = 5.11462616000000E-02 scalar F = 1.18046237440255E+00 scalar rss = 2.16636560000000E-01 scalar r2 = 1.90999039051129E-01 scalar rmse = 1.04076068334656E-01 qui input byte instrum double resist 1 196.3052 1 196.1240 1 196.1890 1 196.2569 1 196.3403 2 196.3042 2 196.3825 2 196.1669 2 196.3257 2 196.0422 3 196.1303 3 196.2005 3 196.2889 3 196.0343 3 196.1811 4 196.2795 4 196.1748 4 196.1494 4 196.1485 4 195.9885 5 196.2119 5 196.1051 5 196.1850 5 196.0052 5 196.2090 end anova resist instrum assert N == e(N) assert df_r == e(df_r) assert df_m == e(df_m) lrecomp e(F) F e(rmse) rmse e(r2) r2 e(mss) mss e(rss) rss