describe                package:psych                R Documentation

_B_a_s_i_c _d_e_s_c_r_i_p_t_i_v_e _s_t_a_t_i_s_t_i_c_s _u_s_e_f_u_l _f_o_r _p_s_y_c_h_o_m_e_t_r_i_c_s

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

     There are many summary statistics available in R; this function
     provides the ones most useful for scale construction and item
     analysis in classic psychometrics.  Range is most useful for the
     first pass in a data set, to check for coding errors.

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

     describe(x, digits = 2, na.rm = TRUE, skew = TRUE, ranges = TRUE)

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

       x: A data frame or matrix

  digits: How many significant digits to report

   na.rm: The default is to delete missing data 

    skew: Should the skew and kurtosis be calculated? 

  ranges: Should the range be calculated? 

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

     In basic data analysis it is vital to get basic descriptive
     statistics.  Procedures such as 'summary' and hmisc::describe do
     so.  The describe function in the 'psych' package is meant to
     produce the most frequently requested stats in psychometric and
     psychology studies, and to produce them in an easy to read
     data.frame. The results from describe can be used in graphics
     functions (e.g., 'error.crosses').

     The range statistics (min, max, range) are most useful for data
     checking to detect coding errors, and should be found in early
     analyses of the data.  

     Although describe will work on data frames as well as matrices, it
     is important to realize that for data frames, descriptive
     statistics will be reported only for those variables where this
     makes sense (i.e., not for factors or for alphanumeric data). 

     In a typical study, one might read the data in from the clipboard
     ('read.clipboard'), show the splom plot of the correlations
     ('pairs.panels'), and then describe the data.

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

     A data.frame of the relevant statistics: 
      item name 
      item number 
      number of valid cases
      mean
      standard deviation
      median
      mad: median absolute deviation (from the median) 
      minimum
      maximum
      skew
      kurtosis
      standard error

_N_o_t_e:

     Describe uses either the mean or colMeans functions depending upon
     whether the data are a data.frame or a matrix. The mean function
     supplies means for the columns of a data.frame, but the overall
     mean for a matrix.  Mean will throw a warning for non-numeric
     data, but colMeans stops with non-numeric data. Thus, the describe
     function uses either mean (for data frames) or colMeans (for
     matrices).  This is true for skew and kurtosi as well.

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

     <URL: http://personality-project.org/revelle.html> 

     Maintainer: William Revelle revelle@northwestern.edu 

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

     'describe.by', 'skew', 'kurtosi', 'pairs.panels',
     'read.clipboard', 'error.crosses'

_E_x_a_m_p_l_e_s:

     describe(attitude)

     describe(attitude,skew=FALSE)   #attitude is taken from R data sets

