I find these references very interesting from like, a 'pedagogical' viewpoint. My typical Business & MBA students, who are by no means mathematically / analytically / statistically inclined, frequently insist on seeing and using the equations, as a means of 'understanding' what they are doing. I can go along with the gag once, but after that, let's have the machines do the work, OK?

As a means of 'understanding,' I think grinding through some examples 'by hand' is a good thing. Whether it really helps those who are seriously math impaired, could be debatable. But I'm willing to try it. Does anyone have experience with a strictly 'pull down menu' approach?

Jay

Phillip Good wrote:

A curious thing, or so it seemed at the time, was a statement Joe Hodges made to a nonparametrics class, "The ideal mathematics lecture would not involve any writing on the blackboard." In an era when, as you note, one need simply pull down a menu and select t-test, it seems instructors of statistics ought to be getting closer and closer to Hodge's goal. Freedman, Pisani, Purves, and Adhikari has only two formula in the first four chapters and pretty much sticks to that formula density throughout.

Donald Burrill <[EMAIL PROTECTED]> wrote:

Reply to OP and the list.

    There used to be a useful book entitled "Computational Handbook of
    Statistics", by Bruning and Kintz; don't recall the publisher.
    Original edition was published about 1970 and I was aware of at
    least a
    third edition some years later; don't know if it's still current, but
    copies might be found in a university library. Probably viewed as not
    useful these days, when if you want a t-test you pull down the "stats"
    menu in a software program, select "t-test", and follow the dialogue
    boxes, and don't have to do the arithmetic "by hand".

    It was devoted to describing how to carry out standard statistical
    techniques; it sort of treated the reader like a computer
    terminal, and
    programmed the reader through each procedure. ("Step 1. List the data
    [showing a useful format for so doing]. Step 2. Add the data in each
    c! olumn." And so on.) For each technique that it described it also
    provided a short list of references, which the reader could consult if
    he wanted to know anything about the statistical theory underlying the
    technique.

    I don't know the Bronstein book, so don't know whether Bruning & Kintz
    might be useful to you or not.

On Sat, 31 Jan 2004, enclume42 wrote:

    > I am looking for a handbook of statistics a bit similar in style to
    > that the Bronstein has for general mathematics.
    >
    > I have a physics background, thus I am familiar with math, but I am
    > missing some statistics terminology and I miss some basic
    statistical
    > methods. Ideally the book should thus cover all what a good graduate
    > statistician should be aware of.
    >
    > For example, I would like to find each classical variant of a t-test
    > described in ~2 pages, with a short introductory text describing the
    > ideas behind the metho! d, followed by a list of the assumptions
    of the
    > method (e.g. normality of data distribution) and then the
    procedure to
    > actually conduct the calculations (in mathematical terms). Examples
    > and references to specific statistical packages should be kept to a
    > minimum.
    >
    > I have been looking for such a book for months, but I always end up
    > finding textbooks in which the essence of the methods is diluted
    into
    > pages of general -even trivial- considerations (which makes me fall
    > asleep), or in specialized books in which the basics are missing
    (the
    > book should start with the definition of the mean).
    >
    > Any suggestion ? :-)

    Bonne chance! -- DFB.
    ------------------------------------------------------------
    Donald F. Burrill [EMAIL PROTECTED]
    56 Sebbins Pond Drive, Bedford, NH 03110 (603) 626-0816
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