"John H" wrote in message
...
On 2 Mar 2004 12:02:01 -0800, (basskisser) wrote:

"John Gaquin" wrote in message
...
"John H" wrote in message

None would be so bold as to compare their meager intellectual
capacity
with your's, Harry. You have demonstrated your acumen and
intellectual
integrity repeatedly. Who could hope to compare?

He just plucks these little gems from one of those "self improvement"
sections of Reader's Digest. Extensive personal research has shown
that
86.7% of those who have read DH Lawrence extensively have required from
three to five years of therapy in order to rejoin society. :-)

Please post the processes used to obtain the above research numbers,
as well as exactly what type of research performed.

He may have used the

He may have used COCHRAN'S APPROXIMATION TO THE BEHRENS-FISHER
STUDENTS' T-TEST. This would probably be appropriate for answering
the question,b'asskisser. Read the following carefully, and notice
that all the available background data must be used. Please pay
particular attention to Subpart 3, b'asskisser. This is where you will
find the information on the necessary degrees of freedom.

Subpart 1. In general. Subpart 2 describes Cochran's
approximation to the Behrens-Fisher Students' t-test. Subpart 3
presents the standard t-tables at the 0.05 level of significance.

Subp. 2. Cochran's Approximation to the Behrens-Fisher
Students' t-test. Using all the available background data (nb
readings), calculate the background mean (XB) and background
variance (sB2). For the single monitoring well under
investigation (nm reading), calculate the monitoring mean (Xm)
and monitoring variance (sm2).

For any set of data (X1, X2, ... Xn) the mean is calculated
by:
X1 + X2 ... + Xn
-
X = ________________
n

and the variance is calculated by:
_ _ _
(X1 - X)2 + (X2 - X)2 ... + (Xn - X)2

s2 = ___________________________________
n-1

where "n" denotes the number of observations in the set of data.

The t-test uses these data summary measures to calculate a
t-statistic (t*) and a comparison t-statistic (tc). The t*
value is compared to the tc value and a conclusion reached as to
whether there has been a statistically significant change in any
indicator parameter.

The t-statistic for all parameters except pH and similar
monitoring parameters is:

If the value of this t-statistic is negative then there is
no significant difference between the monitoring data and
background data. It should be noted that significantly small
negative values may be indicative of a failure of the assumption
made for test validity or errors have been made in collecting
the background data.

The t-statistic (tc), against which t* will be compared,
necessitates finding tB and tm from standard (one-tailed) tables
where,

tB = t-tables with (nB-1) degrees of freedom, at the 0.05
level of significance.

tm = t-tables with (nm-1) degrees of freedom, at the 0.05
level of significance.

Finally, the special weightings WB and Wm are defined as:
sB2 sm2

WB = ___ and WM = ___

nB nm

and so the comparison t-statistic is:
WBtB + Wmtm

tc = ___________

WB + Wm

The t-statistic (t*) is now compared with the comparison
t-statistic (tc) using the following decision-rule:

If t* is equal to or larger than tc, then conclude that
there most likely has been a significant increase in this
specific parameter.

If t* is less than tc, then conclude that most likely there
has not been a change in this specific parameter.

The t-statistic for testing pH and similar monitoring
parameters is constructed in the same manner as previously
described except the negative sign (if any) is discarded and the
caveat concerning the negative value is ignored. The standard
(two-tailed) tables are used in the construction tc for pH and
similar monitoring parameters.

If t* is equal to or larger than tc then conclude that
there most likely has been a significant increase (if the
initial t* had been negative, this would imply a significant
decrease). If t* is less than tc, then conclude that there most
likely has been no change.

A further discussion of the test may be found in
Statistical Methods (Sixth Edition, section 4.14) by G.W.
Snedecor and W.G. Cochran, or Principles and Procedures of
Statistics (First Edition, section 5.8) by R.G.D. Steel and J.H.
Torrie.

Subp. 3. Standard T-Tables 0.05 Level of Significance1.

Standard T-Tables 0.05 Level of Significance1
t-values t-values
Degrees of Freedom (one-tail) (two-tail)

1 6.314 12.706
2 2.920 4.303
3 2.353 3.182
4 2.132 2.776
5 2.015 2.571
6 1.943 2.447
7 1.895 2.365
8 1.860 2.306
9 1.833 2.262
10 1.812 2.228
11 1.796 2.201
12 1.782 2.179
13 1.771 2.160
14 1.761 2.145
15 1.753 2.131
16 1.746 2.120
17 1.740 2.110
18 1.734 2.101
19 1.729 2.093
20 1.725 2.086
21 1.721 2.080
22 1.717 2.074
23 1.714 2.069
24 1.711 2.064
25 1.708 2.060
30 1.697 2.042
40 1.684 2.021

1Adopted from Table III of Statistical Tables for
Biological, Agricultural, and Medical Research (1947, R.A.
Fisher and F. Yates).

STAT AUTH: MS s 116.07 subds 4,4b

HIST: 9 SR 115
Current as of 11/06/03
John H

On the 'Poco Loco' out of Deale, MD
on the beautiful Chesapeake Bay!

For more insight into the process see:
http://www.amazon.com/exec/obidos/tg...18307?v=glance
and
http://www.amazon.com/exec/obidos/tg...lance&n=507846

Have a nice day!

Mark Browne