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| | [[Special:Contributions/173.245.50.73|173.245.50.73]] 05:20, 26 March 2014 (UTC)Adam | | [[Special:Contributions/173.245.50.73|173.245.50.73]] 05:20, 26 March 2014 (UTC)Adam |
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| − | As a layman, I still have no idea what the comic's about. Is it possible to clear it up a lot more? [[User:LogicalOxymoron|LogicalOxymoron]] ([[User talk:LogicalOxymoron|talk]]) 05:37, 28 March 2014 (UTC)
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| | I think this is a comment of the quality of education today - it is difficult to grade students on a distribution curve and even more so when you take into account the distribution curve of the teachers ability. {{unsigned ip|108.162.249.205}} | | I think this is a comment of the quality of education today - it is difficult to grade students on a distribution curve and even more so when you take into account the distribution curve of the teachers ability. {{unsigned ip|108.162.249.205}} |
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| − | :I thought this as well, my interpretation of the comic was Cueball attempting to fit the data with a "Student t-distribution", realizing that the t-distribution poorly fit, and so replaced it with a "Teacher t-distribution" which has a stronger correlation with the data on the piece of paper presumably; the data in question concerning the scholastic success of students. This comic in part seemed to be poking fun at scientists misappropriating the causation of a recognized phenomena. Like the basic statistics example of people finding a correlation in children between tooth decay and vocabulary when, surprise surprise, both tooth decay and vocabulary are strongly correlated with age. {{unsigned ip|108.162.249.214}}
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| | I noticed the teacher's curve is symmetrical, and after further inspection it could be interpreted as an edge detection: high values show where an edge occurs. The two highest peaks would nicely align with the edges of the paper, the next highest peaks fit the edges of the table, and the rest could be approximation artefacts, as they're equidistant and rather insignificant compared to those four. I'm not statistics pro, but maybe that rings someone's bells? [[Special:Contributions/108.162.210.239|108.162.210.239]] 07:56, 26 March 2014 (UTC) | | I noticed the teacher's curve is symmetrical, and after further inspection it could be interpreted as an edge detection: high values show where an edge occurs. The two highest peaks would nicely align with the edges of the paper, the next highest peaks fit the edges of the table, and the rest could be approximation artefacts, as they're equidistant and rather insignificant compared to those four. I'm not statistics pro, but maybe that rings someone's bells? [[Special:Contributions/108.162.210.239|108.162.210.239]] 07:56, 26 March 2014 (UTC) |
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| − | That's the T. No shade. [[Special:Contributions/172.68.132.151|172.68.132.151]] 07:03, 14 May 2021 (UTC)
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| | :Interesting observation. It may play into an age-long legend told and re-told among the students that some teachers grade papers by tossing the whole pile in the air; those sheets that land on the teacher's desk get a pass, those falling to the floor get a fail. Sometimes the story gets modified in such a way that papers falling on the teacher's book (or other object) laying on the desk will get a higher marking than those simply hitting the desk. The latter version would explain the higher sheet-size-apart peaks. [[Special:Contributions/108.162.210.111|108.162.210.111]] 08:57, 26 March 2014 (UTC) | | :Interesting observation. It may play into an age-long legend told and re-told among the students that some teachers grade papers by tossing the whole pile in the air; those sheets that land on the teacher's desk get a pass, those falling to the floor get a fail. Sometimes the story gets modified in such a way that papers falling on the teacher's book (or other object) laying on the desk will get a higher marking than those simply hitting the desk. The latter version would explain the higher sheet-size-apart peaks. [[Special:Contributions/108.162.210.111|108.162.210.111]] 08:57, 26 March 2014 (UTC) |
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| | : Of course, most of the joke is that the distribution is named "Student's", which is not strongly dependent on the nature of the statistics. [[User:Vyzen|Vyzen]] ([[User talk:Vyzen|talk]]) 12:42, 26 March 2014 (UTC) | | : Of course, most of the joke is that the distribution is named "Student's", which is not strongly dependent on the nature of the statistics. [[User:Vyzen|Vyzen]] ([[User talk:Vyzen|talk]]) 12:42, 26 March 2014 (UTC) |
| | ::Okay, it's pretty clear to me now what the Student's t distribution is. I'm still not sure about the punchline though, how does the "Teacher's" t distribution come into play? Does the uneven distribution represent any phenomena in the academic world? Like, as suggested above, is this a joke about grading? [[Special:Contributions/173.245.53.137|173.245.53.137]] 15:05, 26 March 2014 (UTC) | | ::Okay, it's pretty clear to me now what the Student's t distribution is. I'm still not sure about the punchline though, how does the "Teacher's" t distribution come into play? Does the uneven distribution represent any phenomena in the academic world? Like, as suggested above, is this a joke about grading? [[Special:Contributions/173.245.53.137|173.245.53.137]] 15:05, 26 March 2014 (UTC) |
| − | :::Other than the symmetry, I'd almost suggest that the distribution could be real test scores. Typically tests will have a small number of questions worth multiple points and the scores might spike around levels that represent integral numbers of questions done perfectly, with the spaces in-between filled in by part marks. The teacher may have a bias towards giving perfect or zero scores per question. [[User:Vyzen|Vyzen]] ([[User talk:Vyzen|talk]]) 18:53, 26 March 2014 (UTC)
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| | The teacher's t-distribution looks like multiple spikier curves with different centres added together | | The teacher's t-distribution looks like multiple spikier curves with different centres added together |
| | and it doesn't fit the table. [[User:Wwt|Wwt]] ([[User talk:Wwt|talk]]) 13:17, 26 March 2014 (UTC) | | and it doesn't fit the table. [[User:Wwt|Wwt]] ([[User talk:Wwt|talk]]) 13:17, 26 March 2014 (UTC) |
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| | :I don't think he he trying to pull the paper from out beneath the t-distribution. I think he is placing the distribution on top of the paper to see if the data on the paper matches the distribution. In panel 2, he looks at the paper and decides that, no, it doesn't, so then opts to use another distribution - the Teacher's t-distribution and see if that works. The comic may be hinting that the t-distribution in grading, etc (since students and teachers are explicitly listed) is flawed. --[[User:Dangerkeith3000|Dangerkeith3000]] ([[User talk:Dangerkeith3000|talk]]) 15:10, 26 March 2014 (UTC) | | :I don't think he he trying to pull the paper from out beneath the t-distribution. I think he is placing the distribution on top of the paper to see if the data on the paper matches the distribution. In panel 2, he looks at the paper and decides that, no, it doesn't, so then opts to use another distribution - the Teacher's t-distribution and see if that works. The comic may be hinting that the t-distribution in grading, etc (since students and teachers are explicitly listed) is flawed. --[[User:Dangerkeith3000|Dangerkeith3000]] ([[User talk:Dangerkeith3000|talk]]) 15:10, 26 March 2014 (UTC) |
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| − | I may be over-simplifying it, but the 'Teachers' T looks like a reference to the 'double-hump programmer' idea, converted into a T-distribution. The other ideas cover the general principle, but this looks like a specific example as well. [[Special:Contributions/108.162.221.48|108.162.221.48]] 15:47, 26 March 2014 (UTC)
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| − | I don't think the explanation really explains what a T-distribution is at all. I know it's googleable, but the point of an explanation is you shouldn't have to look it up afterwards. I don't like how lately all of the scientific/maths comics seem to be given explanations laden with technical terms that don't actually clarify anything. --[[User:Mynotoar|Mynotoar]] ([[User talk:Mynotoar|talk]]) 17:57, 26 March 2014 (UTC)
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| − | I did a quick calculation using mspaint, and it appears that the Student's t-distribution in the first panel is roughly 5780 px^2 in size; at the same time the area of the "Teacher's t-distribution" in the last panel is approximately 8125 px^2 (or 140% of the Student's distribution). Thus, using the Teacher's t-distribution as Cueball is intent on doing "is both illegal and illegitimate" (illegitimate = no scientific basis for such a distribution; illegal = this it not even a distribution per se). If Cueball goes on and publishes his results based on such approach, they will not be recognized by the international scientific community (except perhaps by Russia, Syria and North Korea). We, readers, therefore express our deep concern over Cueball's methods. [[User:Stpasha|Stpasha]] ([[User talk:Stpasha|talk]]) 18:27, 26 March 2014 (UTC)
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| − | I believe the joke has to do with "fitting data to a distribution": In the first panel, Cueball is trying to adjust the Student's T distribution on top of the data, which could be a play on "fitting" the data to the distribution. Statistically speaking, fitting data to a distribution is often done to figure out how likely the data were to have occurred, under the assumption that the underlying data generating process follows a particular distribution (like the Student's T). It looks like Cueball first tries to fit his data to a Student's T, and is dissatisfied with the fit. He then tries a much more complicated distribution - which, I think is jokingly called a Teacher's distribution on the premise that something to do with teachers is more complicated than something to do with students. The joke is that data often don't fit a simple distribution like the Student's T... they are nuanced and complex, and their underlying data generating process was far more complex. [[User:Amoorthy|Amoorthy]] ([[User talk:Amoorthy|talk]]) 19:50, 26 March 2014 (UTC)
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| − | : By the way, this is related to and compatible with the explanation given by Dangerkeith3000 above.[[User:Amoorthy|Amoorthy]] ([[User talk:Amoorthy|talk]]) 20:26, 26 March 2014 (UTC)
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| − | The title test could be referring to the tests aspiring teachers have to take in the US to get their credentials. It's sort of like a Bar- except you may take it as many times as you wish until you pass. {{unsigned ip|199.27.128.77}}
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| − | :I thought it referred to the practice that some US school systems have of allowing students to take a test (examination) repeatedly until they pass it. [[Special:Contributions/199.27.128.85|199.27.128.85]] 06:38, 30 March 2014 (UTC)
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| − | I predict that the "Teacher's t-distribution" is the new Cow Tools, and those with actual skill in statistics will drive themselves crazy over it. See [http://tvtropes.org/pmwiki/pmwiki.php/Main/CowTools] for clarification. [[Special:Contributions/199.27.130.168|199.27.130.168]] 21:23, 26 March 2014 (UTC)
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| − | Could it be pointed out that the middle of the Teacher's distribution resembles the Tower of Mordor ? Underscoring the role of the Teacher... {{unsigned ip|173.245.52.25}}
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| − | The explain says that the student distribution works when both the sample and the population have the same variance. Isn't that wrong--doesn't the sample tend to have a larger variance than the population under usual/ideal conditions? (I'm assuming the student distribution is meant for usual/ideal conditions.) [[User:Sciepsilon|Sciepsilon]] ([[User talk:Sciepsilon|talk]]) 00:44, 27 March 2014 (UTC)
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| − | : I believe the true variance of a sample should be the same as the true variance of the population. Perhaps you are thinking of Bessel's correction - using "n-1" in the denominator of the formula for estimating sample variance, instead of "n". If so: While it's true that Bessel's correction makes our estimate of the sample variance larger than if we'd used "n", the reason is that using "n" would have created an estimate that was too small - or, otherwise put, biased toward zero. (The Wikipedia article on Bessel's correction has the best explanation I've seen for why this is true - http://en.wikipedia.org/wiki/Bessel's_correction#The_source_of_the_bias.) What's key here is that Bessel's correction is a technique to correct our <i>estimates</i> of variance - the <i>true</i> variance of a sample is really the same as in the population. [[User:Amoorthy|Amoorthy]] ([[User talk:Amoorthy|talk]]) 16:20, 27 March 2014 (UTC)
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| − | My initial take is that in comic the students' understanding of the correct distribution is being evaluated as a function of the teacher's ability. That a poorly educated student reflects the ability of the teacher[[User:ExternalMonolog|ExternalMonolog]] ([[User talk:ExternalMonolog|talk]]) 12:20, 27 March 2014 (UTC)ExternalMonolog
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| − | : This is exactly what I read. I think people are going all sorts of ways with calculating the T distribution. Clearly you need to just look at the graph and say, "looks like we're saying the data matches to the teacher skill set much more than the presumed result set." Joke over. Move on folks.{{unsigned|Sean timmons}}
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| − | :: Is it just me or the Teacher's T-curve looks like Barad-dur to anyone else..? {{unsigned ip|173.245.62.84}}
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| − | I teach college courses, and find that exam scores typically do not fit a t distribution, or any symmetrical distrubution. They more often show several groups, or what statisticians call "modes." This is a source of frustration for a lot of teachers. I saw this comic as showing how far from "normal" a real teacher's distribution is. It seems to be two superimposed periodic functions instead of a distribution. Or Barad-dur.--[[User:Spencer9|Spencer9]] ([[User talk:Spencer9|talk]]) 17:40, 20 June 2015 (UTC)
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| − | When this comic came out, it put me in mind of this article:
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| − | https://deedy.quora.com/Hacking-into-the-Indian-Education-System
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| − | In which it is shown that the indian university entrance scores do not follow a nice smooth distribution, but instead something with spikes at certain key values like the minimum pass mark.{{unsigned ip|108.162.250.157}}
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| − | The comic could have been inspired by cases where a teacher actually forces the entire class to retake the exam because the results distribution don't fit the curve they expected. Example[https://www.youtube.com/watch?v=rbzJTTDO9f4&pp=ygUjdGVhY2hlciBmb3JjZXMgY2xhc3MgdG8gcmV0YWtlIGV4YW0%3D]
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