chisq.pval              package:corpora              R Documentation

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_D_e_s_c_r_i_p_t_i_o_n:

     This function computes the p-value of Pearsons's chi-squared test
     for the comparison of corpus frequency counts (under the null
     hypothesis of equal population proportions). It is based on the
     chi-squared statistic X^2 implemented by the 'chisq' function.

_U_s_a_g_e:

     chisq.pval(k1, n1, k2, n2, correct = TRUE,
                alternative = c("two.sided", "less", "greater"))

_A_r_g_u_m_e_n_t_s:

      k1: frequency of a type in the first corpus (or an integer vector
          of type frequencies)

      n1: the sample size of the first corpus (or an integer vector
          specifying the sizes of different samples)

      k2: frequency of the type in the second corpus (or an integer
          vector of type frequencies, in parallel to 'k1')

      n2: the sample size of the second corpus (or an integer vector
          specifying the sizes of different samples, in parallel to
          'n1')

 correct: if 'TRUE', apply Yates' continuity correction (default)

alternative: a character string specifying the alternative hypothesis;
          must be one of 'two.sided' (default), 'less' or 'greater'

_D_e_t_a_i_l_s:

     The p-values returned by this functions are identical to those
     computed by 'chisq.test' (two-sided only) and 'prop.test'
     (one-sided and two-sided) for two-by-two contingency tables.

_V_a_l_u_e:

     The p-value of Pearson's chi-squared test applied to the given
     data (or a vector of p-values).

_A_u_t_h_o_r(_s):

     Stefan Evert

_S_e_e _A_l_s_o:

     'chisq', 'fisher.pval', 'chisq.test', 'prop.test', 'rel.risk.cint'

