Talk:Hardy–Weinberg principle

message: My objections to using evolution in the assumptions for H-W are twofold.
*The main result of the HWP is that the population does not evolve, in either a micro- or macro-evolutionary sense.  Including evolution in the definition weakens this — it is no longer a result of H-W, the lack of evolution seems to cause HWP.
*On a macro-evolutionary scale, one of the forces listed is actually anti-evolutionary (works against the evolution of new species).  It is still part of the assumptions, but can't truly be considered evolution.
There is enough mis-information about evolution that we need to be careful when writing about peripheral issues. Ted 00:01, 8 March 2006 (UTC)
thread_title: Evolution in the assumptions

message: What F-Statistics are these?  The F-Statistic given by Sewall Wright is
: F = \frac{\operatorname{E}{(f(\mathbf{Aa}))} - \operatorname{O}(f(\mathbf{Aa}))} {\operatorname{E}(f(\mathbf{Aa}))}\!,
which is the normal inbreeding coefficient for a single population.
I will change it unless someone can give me a reference to the equation in the article. Ted 21:29, 10 March 2006 (UTC)
thread_title: F-Statistics

message: I think the description for the degrees of freedom for the Pearson's Chi-squared test needs modification.
Here's the statistical theory description of how to derive the degrees of freedom for the chi-squared
distribution to which Pearson's statistic converges as the amount of data tends to infinity.
The degrees of freedom for Pearson's chi-squared is equal to the difference in the number of parameters associated
with the statistical models that appear in the null hypothesis and the alternative hypothesis.
In the given example, the general probability model describing the proportions of the population bearing
the three different genotype classes AA, Aa and aa is a multinomial with proportions p1, p2 and p3
respectively.  However, p1 + p2 + p3 = 1.0 so p3 is just (1.0 - p1 - p2).  Therefore, the general probability
model contains two independent parameters, p1 and p2.  The parameter space for this model is two dimensional.
Under the null hypothesis that the allele frequencies follow the Hardy-Weinberg law, the classes
AA, Aa and aa occur with proportions p*p, 2*p*q and q*q where p + q = 1.0.  Thus q = (1 - p) so the
restricted probability model contains one independent parameter, p.  Under Ho, p1 = p*p, p2 = 2*p*(1-p)
and p3 = (1-p)*(1-p).  The parameter space for this model is one dimensional.
The Null Hypothesis model has one degree of freedom associated with its model.  The Alternative
Hypothesis has two degrees of freedom associated with its model.  Under the null hypothesis,
Pearson's Chi-squared statistic has a distribution that converges to a Chi-squared distribution as
the amount of data tends to infinity, and the degrees of freedom of that Chi-squared distribution
equals the difference in the dimensions of the parameter spaces associated with the alternative
and null hypotheses, or (2 - 1) = 1 degree of freedom in this case. 
I know the above discussion is not ready for inclusion in the article.  It needs some smoothing over,
but it represents more accurately the statistical theory associated with determining the
degrees of freedom.
The current discussion stating that a degree of freedom was lost because the expected values were estimated
from the observed values is not relevant.  The expected values for Pearson's chi-squared test statistic
for contingency tables always use the observed values to calculate the expected values.
I will attempt to craft a description of how to determine the degrees of freedom by considering the
number of independent parameters under the null and alternative hypotheses and propose a change to
this article.  If anyone more articulate than I can do this, that would be valuable.
Smckinney2718 23:47, 2 November 2006 (UTC)
replies: text: "The expected values for Pearson's chi-squared test statistic for contingency tables always use the observed values to calculate the expected values."  And, because of that, the degrees of freedom is (r-1)(c-1) and not rc-1.  Most likely, the explanation is simply not needed. Genetics411 02:45, 8 November 2006 (UTC)
thread_title:  Degrees of freedom for Pearson's chi square 

message: I'm new to genetics and I'm not sure what a "discrete generation" is.  I did a google on it but its mainly complex papers I don't understand.  What is a discrete generation?  Also, can this be clarified in the article, or at least create a page on the term and link to it from here?  Thanks very much, --Urthogie 15:55, 6 February 2007 (UTC)
replies: text: Discreet means that they are non-overlapping.  So one generation cannot reproduce with the next.  It just makes the maths a bit easier. --I am not a dog (talk) 00:18, 25 March 2008 (UTC)
thread_title:  discrete generations? 

message: I don't think that "It is possible to represent the effects of Natural Selection and its effect on allele frequency on such graphs." really gets across one of the most useful conclusions one can make with a HWP. An additional comment, something in the vain of, "If there is a discrepancy between the HW prediction and an observed frequency of an allele in a population, especially if this discrepancy changes over multiple generations, then that is evidence that the population is evolving" might be appropriate, though (sadly) controversial. —The preceding unsigned comment was added by 66.24.17.198 (talk) 16:54, 3 March 2007 (UTC)
thread_title:  Evolution 

message: I have the impression that this article includes superfluous information about statistics.  Perhaps we should consider an example that is less verbose and simply reference the appropriate entries on statistical analysis.  neffk 06:36, 14 April 2007 (UTC)
thread_title:  Subject-Appropriate information 

message: I'm a bit confused about this graph. It seems to indicate that the frequency of A is q and the frequency of a is p, while the article (in the intro ("Their frequencies are p and q; freq(A)=p and freq(a)=q.") and the Derivation section) says the opposite. So which is right? Also, the graph is not very clear and it might be confusing to someone who didn't understand HWP. I think it should be replaced with something consistent with the article and easier to understand. --Anakata 22:33, 14 June 2007 (UTC)
thread_title:  Image:Hardy-Weinberg.gif 

message: As far as I can see, the curves 1 and 2  on the graph should be based on P representing allele A and q representing allele a . I only discovered that the equation here is back to front when I tried to interpret the graph.
Who else agrees with me?
RogerWooller 11:32, 16 October 2007 (UTC)
thread_title:  The graph of the Hardy-Weinberg equation needs fixing 

message: Nucdesigner1 01:36, 4 December 2007 (UTC)
replies: text: I corrected the error by making a new diagram, using Inkscape (SVG format). I see that I should have made the image area a few pixels larger on each side, and the colors might be a little garish, but it should do. --Johnuniq (talk) 08:43, 26 February 2009 (UTC)
thread_title:  Error in Hardy-Weinberg plot 

message: 1. Under "Example Chi-squared test ...":  Where did the equation for p immediately under Table 3 come from? This website () does HWP differently. Which is correct?
2. The example deals with the genotype distribution in a given generation. How is the genotype distribution determined for succeeding generations? The assumption of constant allele frequencies is valid but each time the genetic pot is stirred to produce a new generation, the AA, Aa, aa distribution is going to change. Hardy's result seems to indicate this.
:First impression. Question withdrawn Virgil H. Soule (talk) 17:25, 16 July 2009 (UTC)
replies: text: Never mind, I worked out the derivation for myself. Turned out to be simpler than I would have thought. I added the derivation and a numerical example to the article to show that Hardy's math does in fact work.--Virgil H. Soule (talk) 17:25, 16 July 2009 (UTC)
thread_title:  Questions 

message: The assumptions do not state that the need of mendelian inheritance, i.e. alleles are equally likely to be inherited. If this is violated (by selfish genes and such), the formulae and so HWP will fail, since if an allele A can act selfishly against a, the Aa hetrozygotes will be produce more AA's than with mendelian inheritance, and less aa's than with mendelian inheritance, and so forth. (138.38.228.25 (talk) 21:26, 16 January 2010 (UTC)
thread_title:  requires mendelian inheritance. 

message: Shouldn't the first item in "Deviations from Hardy-Weinberg equilibrium" be titled "Non-random mating" rather than "Random mating"?  128.97.70.203 (talk) 20:16, 27 April 2010 (UTC)
replies: text: The wording could be improved, but the text makes the point accurately ("When violations of this provision occur...", meaning when mating is not random). Johnuniq (talk) 02:18, 28 April 2010 (UTC)
thread_title:  Random mating 

message: Mendelian genetics "were" rediscovered..., but "it" remained controversial.
Which one is it?
212.126.224.100 (talk) 16:14, 10 November 2010 (UTC)
thread_title:  History -- mendelian genetics 

message: This page has been a great help in my calculation of a chi-squared statistic for a population distribution resulting from a genotyping experiment.  However, I think there is a small (simple) error in the explanation of the chi-squared test results. The article states the following:
:The 5% significance level for 1 degree of freedom is 3.84, and since the χ2 value is less than this, the null hypothesis that the population is in Hardy–Weinberg frequencies is rejected.
In the article on Chi-squared distribution, a table is given that relates χ2 to p-value.  The χ2 for df=1 is indeed 3.84, but χ2 less than 3.84 are insignificant, not significantly significant.  Doesn't this mean that a χ2 value less than 3.84 (and consequently a p>0.05) indicates the null hypothesis (population in HWE) CANNOT be rejected, and so the population is likely in HWE?  Basically a χ2>3.84 (for df=1) should mean that the population differs significantly from HWE.  Please clarify if I am not thinking about this correctly.  If I am correct, the article could be modified to state "cannot be rejected" rather than "is rejected".
Kelly42 (talk) 00:17, 12 December 2010 (UTC)
thread_title: Error in explanation of chi-squared test results

message: I feel it's unnecessary to talk about alleles being dominant and recessive in relation to the Hardy-Weinberg principle. Hardy Weinberg describes alleles at the genotypic level rather than the phenotypic level. This means dominance has no effect on HWE, so describing alleles in this way is at best redundant. I would suggest changing the A and a alleles to a1 and a2
80.7.125.93 (talk) 16:16, 25 April 2012 (UTC)
replies: text: Fine by me. Joannamasel (talk) 19:51, 25 April 2012 (UTC)
thread_title:  Dominance/Recessivity 

message: In the section titled "Deviations from Hardy-Weinberg Equilibrium" the author states that there are "three such violations."  What it is that is being asserted that is violated is a "provision" of random mating.  Not sure what a "provision" is with respect to a principle such as HWP. Don't you mean "assumption?"
At any rate, the next line asserts that there are 3 "violations" of the "provision" but then only lists 1, inbreeding.  ???
BabelBoy (talk) 14:05, 15 July 2012 (UTC)
thread_title:  Error in deviations section 

message: Does anyone know how to pronounce the first syllable of Weinberg? I've heard most people say /wain/, while some say /wen/ or /win/. The guy is German, does that mean it should be /vain/ ? (I don't speak German) Yel D'ohan (talk) 05:45, 26 April 2013 (UTC)
replies: text: In German (I don’t speak it but I can read it and know basic pronunciation) it would be pronounced Vine-berg but in the US it’s often pronounced Wine-berg. I’m taking an advanced genetics class and the professor pronounces it wine-berg. --MadScientistX11 (talk) 20:02, 13 July 2019 (UTC)
thread_title:  Pronunciation? 

message: Based in part on WP:TECHNICAL.  Lead should address the following points in order (in normal prose, I'm not proposing a question and answer format):
* What is it?  Bolded text that matches common redirects important, keep it as non-technical as possible, ideally no more than a short paragraph. Leave technical asides to a paragraph(s) at the end of the lead.  I think the current lead is OK in this regard.
* Why is it important? IMO the lead doesn't address this well.  Copying the text from the intro to the applications section would be a good start.  Also the historical point that it disproved the theory that dominant alleles increase over time. Aside: Regarding earlier talk, I expect (WP:OR for now) that the word "equilibrium" got used precisely to constrast against that idea.
* Example to illustrate the preceding points.  Keep it simple and concrete.  In this context I think the current quadratic formula is OK as the basis, but the presentation could probably be simplified.
* Anything else non-technical?
* Anything technical that needs to be covered up front?
Regarding overall layout:
* Push derivations towards the end, but link to them as soon as a concept is introduced.
* Push history towards the end, it doesn't really matter where exactly, assume those who want it will use the table of contents to find it.
* Don't treat the general case as a generalisation of the quadratic case, instead treat the quadratic case as a concrete example of a general principle (and general formula).
* Bring the applications to the front, before the theory.  Add more examples of how the principle has been used to prove or disprove interesting questions.  No more than two examples (preferably only one) to illustrate each point of interest.
I have no immediate plans to implement any of this (busy with the article that led me here), so if there is consensus, or you want to be bold, anyone reading this should feel free to go ahead.TuxLibNit (talk) 23:51, 9 January 2014 (UTC)
thread_title:  Suggestions for addressing the "too technical" tag 

message: The Hardy-Weinberg principle is not meant for high school biology projects. This is a principle specific to population ecology with regards to genetic dispersal.
I suggest that the average reader researching the work of Mr. Hardy and Mr. Weinberg be directed to an easily read article discussing the fact that they DEVELOPED this principle. Advanced users, those who would understand the statistics of the principle in conjunction to mark-recapture expeditions upon a given population, would be directed to the page we are discussing.192.231.80.99 (talk) 15:36, 26 April 2016 (UTC)
thread_title:  Too technical for most readers to understand; ([[Special:Contributions/192.231.80.99|192.231.80.99]] ([[User talk:192.231.80.99|talk]]) 15:36, 26 April 2016 (UTC)) 

message: I do not understand what note 1 is trying to say and suspect it is nonsense:
: The term frequency usually refers to a number or count, but in this context, it is synonymous with probability.
No probability distribution was mentioned up to this point. Instead we only talked about a population. Given such a population, one can count the number of alleles of type A and divide it by the total to get a number between 0 and 1, which is a frequency and not a probability, since it indeed refers to a count.
Does this footnote really intend to say that in spite of this, the Hardy-Weinberg theory uses the word "frequency" to refer to something else? If so that something else needs to be properly defined, so that we know which probability distribution is being referred to. If not then the footnote is just wrong and should either be removed or replaced by something more correct such as
: by "frequency" we mean the number of alleles of a given type at the given locus, divided by the size of the population.
I'm not an expert on this topic but I sincerely expect that this is what is actually meant.
Although, after that the text refers to an expectation, despite still not having defined any probability distribution. (Perhaps an average was meant, rather than an expectation.) I suspect that the author doesn't know any probability theory and is fundamentally confused about the difference between probabilities and frequencies. This is unfortunate because any model in population genetics involves both, and if you don't know the difference then nothing you say or calculate will make any sense.  I will look elsewhere for information on this topic. This needs attention from an expert.
Nathaniel Virgo (talk) 04:07, 21 May 2023 (UTC)
replies: text: My guess is that the note (which is old, before 2019) was from someone used to the electrical engineering term frequency. There should be a link to Frequency (statistics) somewhere in the article but I'm not sure where it should go as "frequency" is used, well, frequently. Perhaps asking at one of the above wikiprojects would bring help. Johnuniq (talk) 04:35, 21 May 2023 (UTC)
thread_title:  Nonsensical footnote 

message: The maths in the 'Derivation' section relies on a bunch of assumptions that are not even mentioned until the 'Deviations from Hardy–Weinberg equilibrium' section. In particular, none of the maths makes any sense at all unless you know that we're assuming an infinite population. I was completely confused by that and didn't have a clue what was going on. The assumptions need to at least be mentioned before they are used, in order for the article to be any use. I will edit to at least mention the infinite population assumption, which is crucial.
Nathaniel Virgo (talk) 04:40, 21 May 2023 (UTC)
replies: text: OK. Hardy's discussion of the principle is short and can be seen in the sources and here. It lists the assumptions. Johnuniq (talk) 05:40, 21 May 2023 (UTC)
thread_title:  Assumptions listed after they are used