[R] Ignorant lack of bliss : summarise table by column attribute

[Rory Campbell-Lange]

Having read the list posting guidelines I fear my first post is about to
break the rules. Apologies in advance.

We have been asked to produce some graphs of relative performance of 3
groups of people in relation to the trend of their previous performance.
I am neither a mathematician or a statistician, but wondered if R (which
I have been using as a desktop calculator!) and some knowledge from this
list may be able to help.

We have a dataset something like this:

    group | previousavg | lastreading | finalreading
    ------------------------------------------------
    1     | 9.5         | 10          | 12
    1     | 7           | 9           | 11
    1     | 12          | 11          | 12
    2     | 13          | 14          | 16
    2     | 11          | 10          | 9
    3     | 10          | 10          | 10.5
    3     | 8.5         | 10          | 12

I need to produce some graphs typifying the change for each group
between a _projected_ final reading and the final reading given. The
time difference between previousavg and lastreading is 1/2 that between
lastreading and finalreading.

Where I have got to so far:

I have read the result set (less than 200 rows) into a table 'results',
attached it and then rather crudely constructed projected figures :

    results$projected = 
        ((lastreading - previousavg) * 2) + lastreading

then I can see the differentials between projected and finalreading:

    > result$projected - results$finalreading
     [1] -1.4  6.9  1.1  3.4  0.0  3.6 -3.8  0.1 -0.1  0.9  1.2 -3.4 -1.5  0.1  5.6
    [16] -3.3 -1.9  0.9 -3.1  1.5  0.7 -1.6 -0.3  1.1 -0.1 -0.6  1.5  0.2  0.8 -1.0
    [31]  0.8 -0.5  1.9 -4.0 -3.3  3.1  2.8 -0.6  1.2  2.0 -1.9 -1.6 -1.1 -3.9   NA
    ...
     
Aims:

    - Summarise these by groups (I can't work out how to use tapply...)
    - Produce a sensible 'typification' of each group's change in
      relation to the projected figure. I assume this would use a
      statistical algorithm to exclude exceptions.
    - Plot the 3 'typifications' in sensible relation to each other,
      possibly with data points showing the source of these lines.

My sincere apologies if this is completely off-topic for this list. I'm
hoping to learn a little by understanding how certain functions are used
(approaching this like a programmer rather than a statistician.)

If I needed to learn more is the book "Introductory Statistics with R" a
good place to start?

Thanks
Rory

-- 
Rory Campbell-Lange 
<rory at campbell-lange.net>
<www.campbell-lange.net>