npk                   package:MASS                   R Documentation

_C_l_a_s_s_i_c_a_l _N, _P, _K _F_a_c_t_o_r_i_a_l _E_x_p_e_r_i_m_e_n_t

_D_e_s_c_r_i_p_t_i_o_n:

     A classical N, P, K (nitrogen, phosphate, potassium) factorial
     experiment on the growth of peas conducted on 6 blocks. Each half
     of a fractional factorial design confounding the NPK interaction
     was used on 3 of the plots.

_U_s_a_g_e:

     npk

_F_o_r_m_a_t:

     The 'npk' data frame has 24 rows and 5 columns:

     '_b_l_o_c_k' which block (label 1 to 6).

     '_N' indicator (0/1) for the application of nitrogen.

     '_P' indicator (0/1) for the application of phosphate.

     '_K' indicator (0/1) for the application of potassium.

     '_y_i_e_l_d' Yield of peas, in pounds/plot (the plots were (1/70)
          acre).


_S_o_u_r_c_e:

     Imperial College, London, M.Sc. exercise sheet.

_R_e_f_e_r_e_n_c_e_s:

     Venables, W. N. and Ripley, B. D. (2002) _Modern Applied
     Statistics with S._ Fourth edition.  Springer.

_E_x_a_m_p_l_e_s:

     options(contrasts = c("contr.sum", "contr.poly"))
     npk.aov <- aov(yield ~ block + N*P*K, npk)
     npk.aov
     summary(npk.aov)
     alias(npk.aov)
     coef(npk.aov)
     options(contrasts = c("contr.treatment", "contr.poly"))
     npk.aov1 <- aov(yield ~ block + N + K, data = npk)
     summary.lm(npk.aov1)
     se.contrast(npk.aov1, list(N=="0", N=="1"), data = npk)
     model.tables(npk.aov1, type = "means", se = TRUE)

