/*****************************************************************************
*                                                                            *
*   CNF2STD.SPL   Copyright (C) 2000-2001 DSP Development Corporation        *
*                               All Rights Reserved                          *
*                                                                            *
*   Author:      Randy Race                                                  *
*                                                                            *
*   Synopsis:    Converts an alpha confidence level to standard deviations   *
*                                                                            *
*   Revisions:    3 Apr 2000  RRR  Creation                                  *
*                 7 Dec 2001  RRR  Use better INVPROBN function              *
*                                                                            *
*****************************************************************************/

#if @HELP_CNF2STD

    CNF2STD

    Purpose: Converts a confidence level (%) to a standard deviation range

    Syntax:  CNF2STD(alpha)

              alpha - real or series, the confidence level(s) in %, defaults
                      to, 99, a 99% confidence level.


    Returns: a real or series, standard deviation range for the
             given confidence level(s).


    Example:
             cnf2std(99)

             returns 2.5758 the standard deviation range for a
             confidence level of 99%


    Example:
             W1: {99, 98, 97, 96, 95}
             W2: cnf2std(w1)

             W2 == {2.5758, 2.3263, 2.1701, 2.0537, 1.9600}

             the standard deviation ranges for confidence levels
             99%, 98%, 97%, 96%, and 95%

    Remarks:
             CNF2STD uses the built-in INVPROBN function to lookup a Z value
             for a given probability.

    See Also:
             Ivsnormpb
#endif


/* confidence level to standard deviation range */
cnf2std(cnf)
{
        return(invprobn(0.5 + cnf / 200));
}