On Fri, 11 Jan 2002, Dennis Roberts wrote:
if the polls used similar ns in the samples ... i disagree
now, if the white sample was say 600 and the black sample was 100 ... i
MIGHT be more likely to agree with the comment below
consider white goes 10% to 15% up 50%, 5%pts
In sci.stat.consult Chia C Chong [EMAIL PROTECTED] wrote:
: down!!) fit very accurately to the data. The only bit that is not fit is the
: height of the estimated gamma PDF is not high enough. Does this means that
ARe the areas thee same?
In sci.stat.consult janne [EMAIL PROTECTED] wrote:
: I have a correlation formula I don't get to work. And we must use this
: formula on the test. Let me give you an example: Let's say X and Y
If you don't know with x(with a line above) MEANS, you need to STUDY your
text. Also your instructor
Paul R. Swank [EMAIL PROTECTED] wrote:
: Some years ago I did a simulation on the pretest-posttest control group
: design lokking at three methods of analysis, ANCOVA, repeated measures
: ANOVA, and treatment by block factorial ANOVA (blocking on the pretest using
: a median split).
I found that
Bruce Weaver [EMAIL PROTECTED] wrote:
: Paul's post reminded me of something I read in Keppel's Design and
: Analysis. Here's an excerpt from my notes on ANCOVA:
: the analysis of covariance is more precise with correlations greater than
: .6. Since we rarely obtain correlations of this
Sima [EMAIL PROTECTED] wrote:
: Dear List Members,
: I have missed some lectures on statistics due to heavy illness
: and now i got an assignment which i cannot solve.
We all feel sorry for you Sima, but perhaps you should talk to your
instructor about it. He undoubtedly has office hours.
Dennis Roberts [EMAIL PROTECTED] wrote:
: given a simple effect size calculation ... some mean difference compared to
: that is ... can we not get both NS or sig results ... when calculated
: effect sizes are small, medium, or large?
: if that is true ... then what benefit is there to look at
Ivan Balducci [EMAIL PROTECTED] wrote:
: Magnetic resonance versusFacial Pain Total
:Yes No
: Yes 14 5
: No 11 3041
In sci.stat.consult Atul [EMAIL PROTECTED] wrote:
: I have a doubt regarding adjusted r-square
: How do we calculate the adjusted r-square when the error degrees of
: freedom are zero ?
You don't. you will have perfect prediction even for random numbers.
re previous discussion
My old computer program MANOVA has a built in test of parallelism in
multivariate ANCOVA. It's really standard multivariate regression theory
although it isn't widely known. (TW Anderson gave MANOVA and CanR as two
different eigenproblems).
They are easily shown to be
While cleaning my office I found a 1973 paper by Golub and Styan which
says
the matrix X'X is greatly influenced by roundoff errors and is often
ill-conditioned ... An excellent way of solving (the LS equations) is
through an orthogonal triangular decomposition of X.
At a training session,
Gardburyb [EMAIL PROTECTED] wrote:
: Hi all,
: I'm new to the group. I'm doing my dissertation, and I am doing a canonical
: correlation analysis. My question is, what is the best way to compare canonical
The test of parallelism in mancova is an equivalent test
In sci.stat.consult Gordon D. Pusch [EMAIL PROTECTED] wrote:
: Don't do it that way either --- it's notoriously ill-conditioned.
: It's better and more numerically stable to use the singular-value
: decomposition of 'A' to solve this problem.
It's NOT ill-conditioned unless the X'X matrix is
In sci.stat.consult Michael Stembera [EMAIL PROTECTED] wrote:
: the least squares solution is
: AT * A * W = AT * Y (T means Transpose here)
: W = (AT * A)^-1 * AT * Y
yes, but don't do it that way; solve the simultaneous equations
A'Aw = A'y
in general for numbers a to b
subtract a and divide by (b-a)
=
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Robert J. MacG. Dawson [EMAIL PROTECTED] wrote:
YES
: Elliot Cramer wrote:
: I believe the point of the Danes
: was that a placebo should be used in
: research but that physicians should
: ?not?
: think that they can cure people with
: placebos; I agree.
: -Robert
J. Williams mackeral@remove~this~first~yahoo.com wrote:
: Correct me if I'm wrong, but as I understand it, you have the ability
: to alter your diastolic reading by +/- 20 mm Hg for 3 minutes
No; I said I raised it once. I doubt that it lasted long. All sorts of
things raise blood pressure
J. Williams mackeral@remove~this~first~yahoo.com wrote:
My hunch
: is the placebo group would not differ significantly on the diastolic
: reading from the no-treatment group. Even though the placebo patients
: think they are being treated, I wager they can't fake a diastolic
: reading.
It
J. Williams mackeral@remove~this~first~yahoo.com wrote:
In article [EMAIL PROTECTED] you wrote:
:: do you suppose a person receiving a placebo can actually
:: change his/her diastolic reading?
:
:sure; I raised mine 20 points yesterday just thinking about someone
:misusing statistics.
I am not impressed. I don't think much of people who compare placebo with
no treatment; seems stupid to me. I would expect a placebo in any case
in which the evaluation is a human judgement or one's expectation could
reasonably be expected to affect a measured response. Thus I think you
could
Rich Ulrich [EMAIL PROTECTED] wrote:
: - I was a bit surprised by the newspaper coverage. I tend to
: forget that most people, including scientists, do *not* blame
: regression-to-the-mean, as the FIRST suspicious cause
: whenever there is a pre-post design: because they have
: scarce
auda [EMAIL PROTECTED] wrote:
: Hi, all,
: In my experiment, two dependent variables were measured (say, DV1 and DV2).
: I found that when analyzed sepeartely with ANOVA, independent variable (say,
: IV and had two levels IV_1 and IV_2) modulated DV1 and DV2 differentially:
I don't have a clue
Dianne Worth [EMAIL PROTECTED] wrote:
: I have a multiple regression y=a+b1+b2+b3+b4+b5. My Adj. R-sq is .403.
you can't decompose adjusted R-sqs. The only additive decomposition (and
the only decomposition that makes sense) is the stepwise composition of
R-sq,
adding additional variables
In sci.stat.consult Ronald Bloom [EMAIL PROTECTED] wrote:
Herman as usual is absolutely correct; the validity of the Fisher test is
analagous to the validity of regression tests which are derived
conditional on x but, since the distribution does not involve x, are valid
unconditionally even if
In sci.stat.consult d.u. [EMAIL PROTECTED] wrote:
: I now think that the betas would have to be within [-1,+1]. Suppose you do a
: standarized regression with response Y, and have p variables (X matrix) already in.
you're wrong;
1 varb = r sy/sx = r between -1 and 1
but for 2 var
In sci.stat.consult d.u. [EMAIL PROTECTED] wrote:
: Hi everyone. In the case of standardized regression coefficients (beta),
: do they have a range that's like a correlation coefficient's? In other
: words, must they be within (-1,+1)? And why if they do? Thanks!
Only for 1 x variable where it
James Ankeny [EMAIL PROTECTED] wrote:
: My question is, are they saying that the sampling
: distribution of a binomial rv is approximately normal for large n?
:
It's a special case of the CLT for a binary variable with probability p,
taking the sum of n observations
Marina G. Roussou [EMAIL PROTECTED] wrote:
: A Statistics teacher/tutor/professional is needed to complete an 11 lesson
: assignement paper. Each lesson comprises with approximately 5-10 questions.
:what is this for???
=
dennis roberts [EMAIL PROTECTED] wrote:
: anyone know off hand quickly ... what the formula might be for the standard
: error for r would be IF the population rho value is something OTHER than zero?
It's (1/n)*(1-rho^2)^2
=
Elliot Cramer [EMAIL PROTECTED] wrote:
: dennis roberts [EMAIL PROTECTED] wrote:
: : anyone know off hand quickly ... what the formula might be for the standard
: : error for r would be IF the population rho value is something OTHER than zero?
correctiont: the variance is
(1/n)*(1-rho^2)^2
given random assignment the generalizability of results to a population is
not an issue for statistics. It's a question of what a plausible
population is, given the procedure for obtaining subjects
On Thu, 22 Mar 2001, dennis roberts wrote:
using and interpreting inference procedures under
W. D. Allen Sr. [EMAIL PROTECTED] wrote:
: Either the Chi Square or S-K test, as appropriate, should be conducted to
: determine normality before interpreting population percentages using
: standard deviations.
I don't understand why one would want to use the normal distribution for
I'm not clear on what your design is but it seems that
the problem is in the between S effect not within. Note that you only
have 4 df within and 4 dependent variables
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Alexander Tsyplakov [EMAIL PROTECTED] wrote:
: No, regression models can have stochastic and/or discrete
: regressors. I can only agree that regression models have
There are no constraints whatsoever on the x variables for the
significance tests and estimates to be valid. Power is another
Dale Berger [EMAIL PROTECTED] wrote:
: Dear Colleagues,
: A student is evaluating a summer program for junior high students. One of
: the goals was to raise 'self esteem.' Measures were taken before the
there is no good answer. You might look at "problems in measuring
change" edited by
Werner Wittmann [EMAIL PROTECTED] wrote:
: inverting the
: correlation matrix to get the effects was too complicated to compute by
: hand,so Sir Ronald developed the ANOVA shortcut.
hardly. They do have some mathematics in common (through use of dummy
variables which some of us think is for
On Wed, 17 Jan 2001, Bob Wheeler wrote:
I've heard this before -- probably read it in stat
books. It isn't true. Galton worried over the
problem until he understood the statistical
mechanism.
you may abe right; that's why I said apparrently
J. Williams [EMAIL PROTECTED] wrote:
Would this not
: be the same as the offspring of either the very tall or the very short
: among us moving toward an arithmetic average? Is it inconceivable
: that a pair of dullards could produce a Beethoven or a Fermi for
: example? Frankly, I believe old
In sci.stat.edu Rich Ulrich [EMAIL PROTECTED] wrote:
: If it is some other data... When you have multiple replications,
: sometimes you don't want the *mean* -- for "best single performance"
: you might select maximum or minimum. Or you might consider a trimmed
or in a situation where you
In sci.stat.edu Jim Kroger [EMAIL PROTECTED] wrote:
: Hello, I've received some expert help here on a couple previous occasions
: (thanks). I have an issue bothering me, which I'd like to present to you.
: I'm doing a two-way, 2X2 ANOVA. Suppose I have 20 subjects, and each has
: 25 observations
In sci.stat.consult Clark Dickin [EMAIL PROTECTED] wrote:
: I have a significant main effect for both of my DV's and also
: have a significant Interaction among the DV's but I am unable to
: determine where the interaction comes from. More specifically, is there
the multivariate test assures
G?khan [EMAIL PROTECTED] wrote:
: Hi!
: I wonder how the public is evaluating the normal distribution function
I presume that you want the density of a multivar normal distrib. You
don't calculate the inverse; you just need the quadratic form. I think
that Searle's matrix algebra book gives
on the other hand, it is not desirable at all; it is dumb. You would have
no evidence as to the linearity of the regression function
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Instructions for joining and leaving this list and remarks about
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Rich Ulrich [EMAIL PROTECTED] wrote:
: I think you have been exposed to the prejudices of a few
: Experimentalists in psychology and education, who were
: overly-impressed--for a little while, about 30 or 40 years ago--with
: the miracles of "nonparametric analyses which don't need any
:
Marco Antonio Chamon [EMAIL PROTECTED] wrote:
: Hi,
: Everyone has a program (in excel) to performe multiple linear
: regression? If possible, I'd appreciate to have a copy. Thank you in
: advance.
It's an option in Chart under linear trend
[EMAIL PROTECTED] wrote:
: I am told that I can solve for these three unknowns (B1, B2 and B3) by
: doing simple linear regression to obtain "residuals"; from the
: residuals come the unknowns. For example, I know that with just two
: unknowns (B1 and B2) in:
why would you want to?
In sci.stat.consult sofyan2000 [EMAIL PROTECTED] wrote:
: I have conducted a repeated measure mixed two-factor ANOVA on one sample
you shouldn't have
: 1. What statistical ANOVA test can reveal an outlier in my data?
none
: 2. If my test failed the 'homogeneity of variance/ covariance' test,
Jan de Leeuw [EMAIL PROTECTED] wrote:
: I am glad this one is back after a short absence. Likert scales (or
: any other data) "are" not ordinal or interval. Actually, they have no
a good defense is that anova and regression are not very sensitive to
moderate rescaling of a five point scale so
In sci.stat.consult Jason Osborne, Ph.D. [EMAIL PROTECTED] wrote:
: I am testing for partial mediation. I need to know whether the
: unstandardized regression coefficient for variable X predicting Y in one
: regression equation is significantly different from the unstandardized
: regression
I'm sure they print it out along with the correlation matrix
In sci.stat.consult haytham siala [EMAIL PROTECTED] wrote:
: Can someone please tell me how to calculate the SMC (Squared Multiple
: Correlation) in a factor analysis (SPSS)? I am not sure but could it be the
: diagonal of a factor
In sci.stat.consult "Rui Jorge Gonalves" [EMAIL PROTECTED] wrote:
...
this is the same as eta squared which I mentioned before
In sci.stat.consult Lloyd I. Richardson [EMAIL PROTECTED] wrote:
: of dummy variables for categorical variable model testing? Maybe it was
: Kelly, Beggs McNeil that first suggested this technique.
actually it was R.A. Fisher thru use of orthogonal polynomials
I don't understand why you people are making this so complicated; All he
needs to do is draw a Venn diagram
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