Can you describe the conditions, which must be met for a population to be at a Hardy-Weinberg equilibrium?
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In population genetics, the Hardy–Weinberg principle (HWP) (also Hardy–Weinberg equilibrium (HWE), or Hardy–Weinberg law), named after G. H. Hardy and Wilhelm Weinberg, states that, under certain conditions, after one generation of random mating, the genotype frequencies at a single gene locus will become fixed at a particular equilibrium value. It also specifies that those equilibrium frequencies can be represented as a simple function of the allele frequencies at that locus.\n\nIn the simplest case of a single locus with two alleles A and a with allele frequencies of p and q, respectively, the HWP predicts that the genotypic frequencies for the AA homozygote to be p2, the Aa heterozygote to be 2pq and the other aa homozygote to be q2. The Hardy–Weinberg principle is an expression of the notion of a population in "genetic equilibrium" and is a basic principle of population genetics.\n\nThe original assumptions for Hardy–Weinberg equilibrium (HWE) were that the organism under consideration is:\n\nDiploid, and the trait under consideration is not on a chromosome that has different copy numbers for different sexes, such as the X chromosome in humans (i.e., the trait is autosomal) \nSexually reproducing, either monoecious or dioecious \nDiscrete generations \nIn addition, the population under consideration is idealised, that is:\n\nRandom mating within a single population \nInfinite population size (or sufficiently large so as to minimize the effect of genetic drift) \nand experiences:\n\nNo selection \nNo mutation \nNo migration (gene flow) \nThe first group of assumptions are required for the mathematics involved. It is relatively easy to expand the definition of HWE to include modifications of these, such as for sex-linked traits. The other assumptions are inherent in the Hardy-Weinberg principle.\n\nA Hardy-Weinberg population is used as a reference population when discussing various factors. It is not surprising that these populations are static.
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I assume that you mean for p, the only parameter.\n\nIt's k/n where k = number of successes in n trials.
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mostly determined by the genotype and mode of inheritance. Sometimes it can be epigenetic. some rules like mandelian inheritance, random seggregation, imcomplete penetrance, codomminance and give different phenotypes
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See p. 541 of Econometric Foundations by Mittelhammer, Judge and Miller.  Will be a bit tough to explain on Yahoo.  Actually, I don't like this book, but none of my other ones have this.
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Find yourself a z-statistic table and look up critical value in the table.  Check your stats book on how to interpret the table.\nhttp://www.math2.org/math/stat/distributions/z-dist.htm
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When it states the frequency of the dominant allele in a population, think of p as one allele that 36% of the population is carrying. so, we can set p=36%, or .36\n\nThe next part of the problem asks for the frequency not of the recessive allele, but of the recessive trait. In order to carry the recessive trait, the person must have both alleles. The probability that both parents passed down the allele for the person to have the trait, using the multiplicative rule of probability would be q*q. We are solving for q^2 since we are looking for the trait not the allele. \n\n1-p=q\n1-.36=.64\nq*q=.64*.64=0.4096\n0.4096*100%=40.96%
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Yea. Read 'Ishmael' from Daniel Quinn and study/do a project on population. You'll know what I mean if/when you read this defining book. :)
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For the first part, per hour the rate is 30.  so we have lambda = 30, so we know the mean and variance (look at the answer before mine).  To find the Probability the 240th person enters in the 8th hour, find the probability 240 or more people arrive in an 8 hour day, then times that by the probability less than 240 arrive in 7 hours.\n\nso (1-P(<240 in 8))*P(<240 in 7)\n\nRemember, The poisson process is memoryless.\n\nSteve
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Depends on the cell type labile, stable, non regenerative etc
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For an uncertainty x of 0.01 (which your 99% accuracy would be) you need 1/x^2 samples which would be 10000.  This is true for a large population (>>10000).  I believe you still need that many for 20000 population but am only 99% sure.\nSource: Best recollection of a stat course 50 years ago.
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use that at equilibrium : n.p = ni^2\nand from charge neutrality: \n\nn + NA = p + ND
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I predict the value will increase without bound. One factor in  any potential success is the way you integrate around the pole. There could be a strong singularity!
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population and genaration
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Ideally you would want the largest number possible. If you use too few people then there would not be enough variety in their genes.\n\nEventually the entire population's genes would be very similar and the members of the population would have similar strengths and weaknesses eg. if one member of the population is not resistant to a particular virus, then because of the genetic similarity to other members it is quite likely that the entire population would not be resistant. It would be possible for them to be wiped out by a single virus (or other threat).
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You might find the following informative:\nhttp://www2.mtroyal.ab.ca/~igilborn/admn1382/regression/theory/part_b.htm
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Check out "mitosis" in a suitable source (Wikipedia, for example).  The process is a bit long to describe here.
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I've also heard of studies similar to those you're referring to; I agree 100% w/ you that high population density is a pretty feasible reason for homosexuality and violence, these may well be nature's "control mechanisms" for avoiding LOCAL overpopulation. As far as the whole world being overpopulated, I don't agree w/ you.... food production nowadays, for example, could feed more than 100% of the world's population adequately if equally spread among all human beings; furthermore, global birth rates are rapidly declining, which could actually lead to global UNDERpopulation just a few centuries from now.