When I was a young analyst, someone asked if the percentiles I'd
provided were calculated the "right way" or the "wrong way." Using the
cumulative percents is the "wrong way" (obviously, for some values of
"wrong").
The "right way" (for some values of "right" or "correct") calculates the
percentile of the midpoint of the score category and will never be
exactly 0 nor exactly 100.
I calculate percentiles that way. I take the values of the frequency
table and copy them into a spreadsheet.
percentile = ( 0.5 * COUNT + BELOW ) / TOTAL
where COUNT is the frequency of the current score category, BELOW is the
cumulative count of cases with lower scores, and TOTAL is the total
number of cases.
BTW, the other problem that arises is that some scores will be missing.
This is less an issue for OP who just wants percentiles for his
participants/students. One solution is to a single "pseudo count" person
to ever score category (so it's COUNT+1 and BELOW and TOTAL include
these "pseudo" people). I think this is Laplace smoothing.
-Alan
On 3/22/2023 10:18 AM, Peg Whalen wrote:
I believe you could just use the Cumulative Percent off the
Frequencies table
On Wed, Mar 22, 2023 at 10:13 AM Ian McKenzie
<i...@prosocialscience.com> wrote:
Hi all!
Let's say that I have a database of scores by individual: for
example,
Sam has a score of 29 on his math test. I have 140 cases that are
simple like that.
I would like to compute the percentile score for each individual such
that a case would look like this;
Name Score Percentile
Sam 29 39
...
I'd like the same kind of information for all 140 cases.
Anybody know how to do this? I would truly appreciate a solution.
Thanks
Ian
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