Talk:Percentile rank

merge with percentile
agree

I disagree, keep it as it is. If someone wants to look up 'percentile rank' then that's what they should be able to do. The explanation is clear and lucid and I really don't see what the problem is. Nick mallory (talk) 08:38, 9 May 2009 (UTC)[reply]

I also disagree, keep it seperate as it's a seperate concept. 24.222.205.6 (talk) 15:40, 29 May 2009 (UTC)[reply]

A link should be set with the term Quantile and cumulative distribution function. Its contrast with percentile and quantile should be explained. I am not familiar with current term, but note that the function 'percentrank' in excel gives 0% for the minimum value and 1% for the maximum value. In contrast, different formulas exist to calculate the quantile of an observed value. Statistica for instance proposes [(i - rankadj)/(n + nadj)]to calculate the quantile ot the i'th rank. With rankadj = .375 and nadj = .25 as default. 13:16, 29 July 2009 (UTC) Just a humble junior statistician —Preceding unsigned comment added by 194.7.152.194 (talk)

Previous version referred to "cumulative frequency" for the count of scores below the item of interest. But it isn't the cumulative freq. It is a simple count. —Preceding unsigned comment added by 204.210.156.95 (talk) 21:21, 23 June 2010 (UTC)[reply]

This text is in error in that it describes percentile ranks as normally distributed and NCEs as having rectangular distributions. As I understand them, Normal Curve Equivalents (NCEs) are a type of standardized score with a mean of 50 and a standard deviation of 21.06. NCEs have a range of one to 99 and in many ways look a lot like percentile ranks -- including having a rectangular distribution. PRs are ordinal and have a rectangular distribution, which is the central problem in their analysis. Please correct me if I'm wrong Andrewt99 (talk) 16:23, 3 August 2010 (UTC)Andrew [andrewt@ucla.edu][reply]

The first two sentences are in direct conflict with each other. Either a score at the 75th percentile is "greater than 75% of the scores" or it is "the same or [higher] than" scores in its frequency distribution. I came here to confirm what I thought I knew, only to be confounded by the contradiction of the two explanations. Please fix it. 64.85.248.115 (talk) 20:24, 3 December 2010 (UTC)[reply]

Contradiction in definition

The first two sentences of the article read (my emphasis):

"The percentile rank of a score is the percentage of scores in its frequency distribution that are equal to or lower than it. For example, a test score that is greater than 75% of the scores of people taking the test is said to be at the 75th percentile, where 75 is the percentile rank."

According to the first sentence, a percentile rank (PR) of 75 means that 75% of the population have an equal or lower score, i.e. PR 75 >= 75 %. According to the second sentence, a percentile rank of 75 means that 75% of the population have a lower score, i.e. PR 75 > 75%.

Which is correct?

I entered "Edit" mode with exactly the same question. I don't know who 'creates' these definitions, but "equal to or greater than" is NOT the same as "greater than!" The contradiction is obvious but the resolution is not obvious" — Preceding unsigned comment added by Jimkay317 (talk • contribs) 21:59, 3 July 2020 (UTC)[reply]

I also found an error in the (possibly revised?) intro where CF and CF' are defined as the same thing, the article reads:

"where CF—the cumulative frequency—is the count of all scores less than or equal to the score of interest, F is the frequency for the score of interest, and N is the number of scores in the distribution. Alternatively, if CF' is the count of all scores less than the score of interest"

CF and CF' are (I believe) supposed to be exact opposites.

Possible error is underlined, also please note I am no Wikipedia user, I'm not sure if this is the correct place to leave this note. 176.29.229.239 (talk) 10:32, 25 August 2024 (UTC)[reply]