shapiro.test              package:stats              R Documentation

_S_h_a_p_i_r_o-_W_i_l_k _N_o_r_m_a_l_i_t_y _T_e_s_t

_D_e_s_c_r_i_p_t_i_o_n:

     Performs the Shapiro-Wilk test of normality.

_U_s_a_g_e:

     shapiro.test(x)

_A_r_g_u_m_e_n_t_s:

       x: a numeric vector of data values. Missing values are allowed,
          but the number of non-missing values must be between 3 and
          5000.

_V_a_l_u_e:

     A list with class '"htest"' containing the following components: 

statistic: the value of the Shapiro-Wilk statistic.

 p.value: an approximate p-value for the test.  This is said in Royston
          (1995) to be adequate for 'p.value < 0.1'.

  method: the character string '"Shapiro-Wilk normality test"'.

data.name: a character string giving the name(s) of the data.

_S_o_u_r_c_e:

     The algorithm used is a C translation of the Fortran code
     described in Royston (1995) and found at <URL:
     http://lib.stat.cmu.edu/apstat/R94>. The calculation of the p
     value is exact for n = 3, otherwise approximations are used,
     separately for 4 <= n <= 11 and n >= 12.

_R_e_f_e_r_e_n_c_e_s:

     Patrick Royston (1982) An extension of Shapiro and Wilk's W test
     for normality to large samples. _Applied Statistics_, *31*,
     115-124.

     Patrick Royston (1982) Algorithm AS 181: The W test for Normality.
     _Applied Statistics_, *31*, 176-180.

     Patrick Royston (1995) Remark AS R94: A remark on Algorithm AS
     181: The W test for normality. _Applied Statistics_, *44*,
     547-551.

_S_e_e _A_l_s_o:

     'qqnorm' for producing a normal quantile-quantile plot.

_E_x_a_m_p_l_e_s:

     shapiro.test(rnorm(100, mean = 5, sd = 3))
     shapiro.test(runif(100, min = 2, max = 4))