-------- Mike Wogan writes --
----- Original Message -----
From: Mike Wogan <[EMAIL PROTECTED]>
To: Luv 2 muah 143 <[EMAIL PROTECTED]>
Cc: <[EMAIL PROTECTED]>
Sent: Wednesday, December 08, 1999 11:16 AM
Subject: Re: could someone help me with this intro to stat. problem
| On 8 Dec 1999, Luv 2 muah 143 wrote:
|
| > 5 of 10 volunteers are randomly selected to receive self-defense training. The
| > other 5 receive no training. At the end of the training period, all subjects
| > complete a self-confidence questionnaire.
| >
| > a.) Is there a difference in self-confidence between the 2 groups (p<.01)?
| >
| >
| > b.) What are the effects of self-defense traing on self-confidence (I'm
| > assuming a two-tailed test?). Explain analysis
| >
| > Please help, I can't figure it out...my mind has gone blank!!!!
|
| Without a pre-test measure of self-confidence, taken prior to the
| training, even if there is a significant difference post-training, it's
| not possible to tell whether the difference is the result of the training
| or was there to begin with.
|
| If there is a pre-post measurement of self-confidence, then you need a
| mixed model Anova, with Training vs. No Training as the between groups
| factor and Pre-Post as the within groups factor.
|
| Mike
|
---------------------- End of Mike's message --
Great suggestion, Mike --
" Without a pre-test measure of self-confidence, taken prior to the
training, even if there is a significant difference post-training, it's
not possible to tell whether the difference is the result of the training
or was there to begin with. "
The question "IN NATURAL LANGUAGE" might be stated slightly differently as:
(1) For subjects who have the SAME PRE-TEST MEASURE OF SELF-CONFIDENCE but
have DIFFERENT TRAINING (i.e., TRAINING vs NO-TRAINING) is their a DIFFERENCE
IN THE EXPECTED POST-TEST MEASURE OF SELF-CONFIDENCE.
or perhaps
(2) If their is a difference between the two groups, is the difference the SAME FOR
ALL VALUES OF THE PRE-TEST MEASURE OF SELF-CONFIDENCE?
In these "NATURAL LANGUAGE FORMS" of the research questions
the researcher should be able to write an ASSUMED MODEL
that allows for the expression of the hypotheses of interest in terms OF PARAMETERS OF
THE ASSUMED MODEL. Then the restrictions implied by the questions of interest can be
imposed on the ASSUMED MODEL to obtain a RESTRICTED MODEL to test the hypotheses.
AND NOW FOR MY "STANDARD SERMON"!
The approach described as:
" If there is a pre-post measurement of self-confidence, then you need a
mixed model Anova, with Training vs. No Training as the between groups
factor and Pre-Post as the within groups factor."
DOES NOT COMMUNICATE clearly how to proceed.
The reader has to learn the meaning of:
"mixed model Anova"
"between groups factor"
"Pre-Post as within groups factor."
or be able to locate a "packaged" algorithm that sounds similar to:
Mixed model Anova, with Training vs. No Training as the between groups
factor and Pre-Post as the within groups factor."
Another "advisor" might suggest:
"Do an Analysis of Covariance, with the Pre-Test Measure of Self-Confidence
as the Covariable".
As before, the researcher must know the meaning of the advice or locate
a "package" that is labeled as "COVARIANCE ANALYSIS".
This second approach is dangerous since many "packaged" COVARIANCE
ANALYSIS" algorithms my not allow the researcher to answer the questions of
interest, e.g. question #2 above.
And even if such "packages" are located the researcher may not be able to
verify that the answers produced by the "package" are related to the natural
language questions of interest.
In summary, statistics instruction should give students (researchers) the power to:
1.State their research questions in NATURAL LANGUAGE so
that normal humans can understand.
2.Create models that allow the researcher to express hypotheses of interest.
3.Translate NATURAL LANGUAGE questions into RESTRICTIONS on
parameters of the ASSUMED MODEL.
4.Impose the RESTRICTIONS to obtain a RESTRICTED MODEL.
5. Verify that the RESTRICTED MODEL has the RESTRICTIONS IMPLIED BY THE
QUESTIONS OF INTEREST.
5.Use information from the ASSUMED and RESTRICTED MODELS to HELP
make decisions about the questions of interest.
Hopefully, (Luv 2 muah 143) is being provided the opportunity to do the above!!
Reasonably talented high school students should be given to power to do this.
:-)
--- Joe
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