/* NIST StRD benchmark from http://www.nist.gov/itl/div898/strd/ Univariate Summary Statistics Difficulty=Lower N=50 Observed File Name: mavro.dat Dataset Name: Filter Transmittance Description: This is an observed/"real world" data set consisting of 50 transmittance measurements (at a sampling rate of 10 observations per second) from a filter with a nominal value of 2. The experimenter was Radu Mavrodineaunu, a member of the chemistry staff at NIST. We here use this data to test accuracy in summary statistics calculations. Stat Category: Univariate: Summary Statistics Reference: None Data: "Real World" 1 Response : y = transmittance 0 Predictors 50 Observations Model: Lower Level of Difficulty 2 Parameters : mu, sigma 1 Response Variable : y 0 Predictor Variables y = mu + e Certified Values Sample Mean ybar: 2.00185600000000 Sample Standard Deviation (denom. = n-1) s: 0.000429123454003053 Sample Autocorrelation Coefficient (lag 1) r(1): 0.937989183438248 Number of Observations: 50 */ clear scalar N = 50 scalar mean = 2.00185600000000 scalar sd = 0.000429123454003053 scalar rho1 = 0.937989183438248 qui input double y 2.00180 2.00170 2.00180 2.00190 2.00180 2.00170 2.00150 2.00140 2.00150 2.00150 2.00170 2.00180 2.00180 2.00190 2.00190 2.00210 2.00200 2.00160 2.00140 2.00130 2.00130 2.00150 2.00150 2.00160 2.00150 2.00140 2.00130 2.00140 2.00150 2.00140 2.00150 2.00160 2.00150 2.00160 2.00190 2.00200 2.00200 2.00210 2.00220 2.00230 2.00240 2.00250 2.00270 2.00260 2.00260 2.00260 2.00270 2.00260 2.00250 2.00240 end summarize y assert scalar(N) == r(N) lrecomp r(mean) mean sqrt(r(Var)) sd gen time = _n tsset time corrgram y, lag(1) lrecomp r(ac1) rho1