stackloss                package:base                R Documentation

_B_r_o_w_n_l_e_e'_s _S_t_a_c_k _L_o_s_s _P_l_a_n_t _D_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     Operational data of a plant for the oxidation of ammonia to nitric
     acid.

_U_s_a_g_e:

     data(stackloss)

_F_o_r_m_a_t:

     'stackloss' is a data frame with 21 observations on 4 variables.

       [,1]  'Air Flow'    Flow of cooling air
       [,2]  'Water Temp'  Cooling Water Inlet Temperature
       [,3]  'Acid Conc.'  Concentration of acid [per 1000, minus 500]
       [,4]  'stack.loss'  Stack loss

     For compatibility with S-PLUS, the data sets 'stack.x', a matrix
     with the first three (independent) variables of the data frame,
     and 'stack.loss', the numeric vector giving the fourth (dependent)
     variable, are provided as well.

_D_e_t_a_i_l_s:

     "Obtained from 21 days of operation of a plant for the oxidation
     of ammonia (NH3) to nitric acid (HNO3).  The nitric oxides
     produced are absorbed in a countercurrent absorption tower".
     (Brownlee, cited by Dodge, slightly reformatted by MM.)

     'Air Flow' represents the rate of operation of the plant. 'Water
     Temp' is the temperature of cooling water circulated through coils
     in the absorption tower. 'Acid Conc.' is the concentration of the
     acid circulating, minus 50, times 10: that is, 89 corresponds to
     58.9 per cent acid. 'stack.loss' (the dependent variable) is 10
     times the percentage of the ingoing ammonia to the plant that
     escapes from the absorption column unabsorbed; that is, an
     (inverse) measure of the over-all efficiency of the plant.

_S_o_u_r_c_e:

     Brownlee, K. A. (1960, 2nd ed. 1965) _Statistical Theory and
     Methodology in Science and Engineering_. New York: Wiley. pp.
     491-500.

_R_e_f_e_r_e_n_c_e_s:

     Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) _The New S
     Language_. Wadsworth & Brooks/Cole.

     Dodge, Y. (1996) The guinea pig of multiple regression. In:
     _Robust Statistics, Data Analysis, and Computer Intensive Methods;
     In Honor of Peter Huber's 60th Birthday_, 1996, _Lecture Notes in
     Statistics_ *109*, Springer-Verlag, New York.

_E_x_a_m_p_l_e_s:

     data(stackloss)
     summary(lm.stack <- lm(stack.loss ~ stack.x))

