On Sat, 29 Sep 2012 05:30:40 -0700, William Scott wrote:
>
>I think the prediction from Karl's observation is that if the obtained t
>is 1.0999783 and the critical t is 1.11100003, then many students would
>make a mistake in choosing which was larger.

See, If I presented these two numbers, the first thing I would do is
tell the students to round the two numbers to (a) the same number
of decimal values, and (b) to the number of decimal values that
maintains information about the difference between the two numbers.

In the case above, I would ask students to round the two numbers
to two decimals values, so,
1.0999783 becomes 1.10
and
1.11100003 becomes 1.11

Which number is larger?  Perhaps one of the things we need to do
is show how to increase the signal to noise but point out how to
simply some expressions.
NOTE:  In Excel, for the t-test, they provide a ridiculous number of
decimal values, like above, and I tell students to (a) highlight the cell,
(b) right click to get the list menu, (c) select cell format, and (d) click
on "number" format and use 3 decimal values for the obtained statistic,
critical statistic, and p-value.  Seems to reduce confusion but I haven't
systematically studied this.

>I am gob-smacked. Karl's observation, if true, might explain many things
>that until now have been mysterious to me.

Perhaps.  Then again, maybe a review of fractions, proportions, and
percentages is in order if these are not covered in some detail.

-Mike Palij
New York University
[email protected]


>>> Michael Palij  09/29/12 7:08 AM >>>
When I teach statistical inference, say with t-tests, I emphasize that
there
are two rules that they can follow and that both lead to the same
conclusion:

(1) Rule 1 for two-tailed t-tests:

If | obtained t-value | is greater than | critical t-value |,
then reject the null hypothesis (else fail to reject).
NOTE #1: the use of "| |" is for absolute value, so the obtained
t-value, regardless of sign has to be larger than the critical
t-value (which might be obtained from a table or, say, Excel's
t-test output which provides both crit t and prob(obt t-value).
NOTE #2: the same rule holds for two-tailed tests for the
Pearson r/correlation coefficients.
NOTE #3:  for one-tailed t-text or Pearson r or F-values or
Chi-square, the rule become "if obtained statistic is greater
than critical statistic, then reject null hypothesis".
NOTE #4.  I make sure that students understand the word
form of the rule before focusing on the more abstract formula
representation.

(2) Rule 2 for tow-tailed t-tests

If Probability(obtained statistic) is less than alpha (= .05),
then reject the null hypothesis (else fail to reject).
NOTE #1:  I emphasize that the numbers for the two rules
go in opposite directions:  you want small probabilities and
large test statistic values.
NOTE #2:  I show a figure of the t-test distribution or
from Glass & Hopkins 3ed, Table Fig6-5-Normal Curve,
which shows the area under the curve. It's a page long
figure with a graphic for the standard normal curve at the
top of the page and several x-axes below, including the
SAT, GRE, and the Wechsler and Stanford-Binet intellligence
scales.  I point out that the y-axis represents relative frequency
and as you go further from the mean, the relative frequency
or probability of a value decreases.  So, I can ask
"Which percentage of values of z, T-score, SAT, GRE, Weschler,
or Standford fall above one standard deviation above the mean."
What values cut off the top 5% or 10% (a table is used for
this).  I emphasize that the more "extreme" the measurement,
the less likely values that larger or larger will occur.
NOTE #3:  I show that in Excel that the t-test procedure
provides both the critical t value (for use with rule #1) and
the probability of the obtained t-value which should be compared
against alpha.  I also show that in SPSS, only the probability
of the obtained t-value is given, so one has to use rule.
I point out that if one calculates the t-value by hand, they
have to use rule #1.

I think somewhere along the way they learn:

As the obtained statistic increases in absolute value, its
probability decreases.  We can then ask either (a) is the value
of the obtained statistic *greater than* some threshold (critical value)
or (b) is its frequency of occurrence (p-value)  *less than"
some threshold value represented by alpha.  The choice of one
rule over the other depends upon how the values are obtained
(i.e., by hand, by Excel, by SPSS, etc.) and we should apply
the appropriate rule for the information we have at hand.

-Mike Palij
New York University
[email protected]


On Sep 28, 2012, at 7:16 PM, Wuensch, Karl L wrote:
          Nope -- my TA would put two numbers up on the board, like .05
and
.032, and ask them, in words, which is lower * or he would put one
number up,
like .046, and ask whether it was less than or more than .05.

Cheers,
----------------------- Original Message --------------------
On Friday, September 28, 2012 6:11 PM. Beth Benoit wrote:
Karl,
Is it possible they're having trouble with the < vs. the >?

I'd be willing to bet that most Americans - no, slash that - most people
struggle with what those two signs represent.  I know, it "ain't rocket
science," but I suspect a lot of people never had that explained to
them.

Please say that's what it really is.  ;-)

On Fri, Sep 28, 2012 at 5:43 PM, Wuensch, Karl L
> wrote:
     I am not the greatest fan of NHST, but do my duty to teach it.  For
a good
while now I have been disturbed that a substantial proportion of my
undergraduate students never figure out how to decide whether or not a
test is
significant.  I tried stressing that p is a measure of the goodness of
fit
between the data and the null, that p is like the strength of evidence
in
support of the accused null defendant in statistical court, and so on.
Nothing
seemed to help much.

        Now one of my teaching assistants has discovered why.  Given two
numbers, these students are unable to identify which is smaller.  No, I
am not
kidding.  Yes, this involves numbers between 0 and 1.  My TA spend half
an hour
trying to teach them how to tell which is the smaller of two numbers,
without
great success.

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