can someone clearly explain the difference between the principle of segregation and independent assortment?
151409
Mendel's First Law (Segregation) states that during gamete formation, each member of an allelic pair (the two 'copies' of a gene) separates from the other member and forms the "genetic supply" of the gamete. That is to say, as each allele is on one of a pair of homologous chromosomes, they will separate from each other during meiosis. \nThis may appear as very basic, but the realization that there were _pairs_ of "factors" (the term 'allele' did not exist in Mendel's time) that separated and then could combine was important because until then, it was thought that inheritance meant some kind of "blend" between elements from both parents. It was very difficult to figure out how, for instance, a flower color that skipped a generation and then appeared again could remain as a discrete element (the reasoning was: if I mix red and white plants, I'll get plants with rose color. Mixing rose with red or white should yield lighter or darker color, but not the originals).\n\nThe Second Law (Independent Assortment) can only be understood when studying _more than one_ allelic pair. The simplest case is the dihybrid cross, in which you analyze the outcome of a cross with respect to 2 different allele pairs. What Mendel found is that the segregation of the alleles of one allelic pair is independent of the segregation of the alleles of another allelic pair. That is to say, if one pair codes for flower color and the other for seed size, in the 2nd generation you will get all the possible combinations of these allele pairs. Remember we're talking of genotypes and _not_ phenotypes (that is, all the alleles will be present, but some will not be 'visible'). \nThe 2nd law works perfectly when the pairs of alleles in question are situated on different chromosomes. If the two pairs are on the same chromosome, there are more possibilities of certain combinations to occur; this is called genetic linkage.
310115
This is an easy derivation. \n\nMultiplicative Principle: \nOne fundamental principle of counting is that if you have n of one type of object (N) and m of another type of object (M), then the number of ways to pair objects of type one with objects of type two with regard to order is n*m. This is argued by saying that one can first pair one of the N-type objects with all of the M type objects for m pairs, and then do the same for the remaining N type objects, giving m + m + ... + m n times, or n*m pairings. \n\nPermutations:\nSuppose you have k objects and you want to know how many ways you can order them in a line. You have k ways to choose the first object, k - 1 ways of choosing the second object, and so forth until you run out of objects. By the fundamental principles of counting, this makes the number of possible orderings k*(k - 1)*...*1 = k! which we will call P(k).\n\nCombinations:\nSuppose the number of combinations of k objects out of n objects without respect to order chosen is C(n, k). If we wanted to count order, we would multiply each combination by the number of ways it could be permuted (by the fundamental principles of counting). Let P(k) be the number of ways of ordering k objects (this is just k! = k*(k-1)*...*1 ). Thus P(k)*C(n, k) is the number of ways one could choose k people out of n people with regard to order. \nBut we can easily count this number another way. The number of possible choices for the first person is n, for the second person n-1, and so on until we reach n - k + 1. Thus, we get the equation P(k)*C(n, k) = n*(n - 1)*...*(n - k + 1) = n!/(n - k)!. Solving for C(n, k), we get C(n, k) = n!/[P(k)(n - k)!] = n!/[k!(n - k)!].
594843
Recombination (I presume this is what you're talking about) can do both. It creates new combinations of alleles at different gene loci that might be especially advantageous in a particular environment. The down side is that it can separate them also, so a parent that has a good combination will produce some offspring that don't have the combination because recombination has separated them in the gametes.\n\nI hope this is what you were asking about.
285327
Your argument has some assumptions, assertions, and logic that are not sound.\n\nFirst of all, you only multiply probabilities together when they are independent variables - it would be easy to argue that many of the items that you mentioned are interdependent.\n\nAlso, I think you misunderstand what evolution of species is proposing.  Evolution does NOT depend on luck - it is instead an observation that lucky organisms survive and pass on their properties to their descendants.\n\nConsider bacteria - almost all mutations are harmful but a few bacteria have lucky mutations that make them immune to penicillin.  If penicillin is used on bacteria, only these lucky ones survive - and most of their descendants inherit the the same immunity-mutation.  \n\nThe original mutation is luck - the environment then selects and a small set of traits due to beneficial mutations persists.  And THAT is not luck, that is selection.  That's why the process is called "Natural Selection".  \n\nSadly, this is why almost all bacteria were zapped by the early antibiotics, and now (only 60 years later) we have hundreds of resistant strains.
808852
Sorry to say, you better pass on this data set.  \n\nNote that each row of numbers totals 100, as these are percentages, so the variables are correlated, and have limited application.\n\nI think your professor wants two of the variables to be somewhat independent, meaning one is not a function of the other.  Such as gas mileage and price, for example, if you had a list of automobile makes.\n\nRatio variables are those in which the ratio of two of the numbers have meaning, such as miles per gallon, for example.  If car A gets 15 mpg and car B gets 20 mpg, you can take the ratio of the two: 15/20 and compute 0.75, meaning car A gets 75% of the mileage of car B.
753055
This is sampling without replacement and without regard to order.\n\nIt's given by the binomial coefficient:\n\nfor n items, choosing k at a time\n\nnCk means n choose k \n\nor \n\n    n!\n-----------  (this is a division)\n(n-k)!k!\nNote that you can get these from Pascal's triangle, nth row, kth column.\n\nSo, 4C2 is 6:\n\nAB\nBC\nCD\nDA\nAC\nBD
168454
WilliamLCB is correct about the when.  The why is described in some detail at the Mathworld link below.  The summary is that dividing by (n-1) for the sample variance is required to give you a *unbiased* estimator for the population variance.
324822
Segregation in cell division, when it goes correctly, results in each meiotic daughter cell having half of the genetic material of the parent.  The catch is, however, that there is no rhyme or reason a certain chromosome will go one way or the other.  So a child will share on average 50% of their geenetic material with each parent.\n\nIn terms of probability, I'm not certain what you mean, so I'll try to just give you my take on it.  If you're talking about the probability of the offspring having a certain allele when the parent is heterozygous, the probability is 50%.  There's a 50/50 chance that when the chromosomes segregate, the one with the allele in question will go to the offspring.  If you've ever done a Punnett square, you can see this: the allele in question will be present in 2 of the 4 boxes, or half of the total.\n\nDoes that help?
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With this method of selection the offspring from a crossing are planted at planting densities equal to commercial planting densities. During this period, which may include a number of generations, the level of homozygosity in the bulk population increases.\n\nThis method is simple and cheap and involves less work than pedigree selection in the earlier generations. It is necessary to plant large populations to ensure that the best segregates are selected when selection starts. Segregating generations are subjected to another single plant selection step. Fewer records are kept during earlier generations than with pedigree selection. This type of selection is especially carried out with crops which are usually planted at high planting densities, e.g. small grain crops.
699803
There are two type of alleles: dominant and recessive.\n\nThe rule of dominance is basically that if dominant is present in the allele, the phenotype (appearance) will not show the recessive gene.\n\nIn Mendel's pea plant experiment, his dominant was purple flower  (PP) and recessive was white flower (pp). \nWhen he crossed purple with white, he got all purples, with genotype (gene) of Pp. Since purple is dominant and is present in genotype, the flower is purple.
240034
Oh, is someone trying to do their homework online?\nWell let me get out my best shot, this was like 300 years ago. so anyway:\n\nMixture is a combination of two or more different particles that do not react one another. For example salt and sugar.\n\nSolution is a homogeneous mixture in which one substance (the solute) is dissolved in another substance (the solvent). Example: sugary water (water as the solvent plus sugar as the solute produces the solution of sugary water\n\nA solution is always a mixture because you have two or more ingredients that dont' react with one another, so its always a mixture because there are two or more reacting ingredients. However, not every mixture is a solution, because there are two ore more ingredients however, they dont get dissolved or mixed with one another.
686085
Okay, genotype II splits into I and I.  Genotype IAIB splits into IA and IB.  Make your square.\n\n     I        I\nIA  IIA      IIA\n\nIB  IIB      IIB\n\nYour possible solutions are types A or B only
705668
the retention times are longer for everything. The gas flow rate is the only variable decider in the speed of transit through the columns. Slower flow means slower movemnt independent of column interactions\n\nThe separation should theoretically be better for everything besides the components that don't interact at all with the column. They come out at dead/void volume anyway. The other components are better separated because the slower flow rate means they have more time to interact with the stationary phase and so the differences in elution rate become more pronounced.
106376
Also, if you agree that the formula for the number of combinations of n objects taken r at a time is\n\nn!/(r!(n-r)!)\n\nand that there is only one way to get a combination of n objects taking all n at a time, you'd get\n\nn!/(n!(n-n)!)  or n!/(n!0!), or canceling, 1/0! which must equal 1.\n\nSo 0! must equal 1.  More of a demonstration than a proof but it's easy to understand.
809259
The law of segregation was formed by Gregor Mendel in the early 1860's.   The law basically says each organism contains two factors for each trait, or allele.  The factors segregate or separate in formation of gametes.   During meiosis, each gamete contains one factor for each trait.  When two games combine during fertilization, the offspring have two factors controlling a specific trait (one from mom, and one from dad).
105345
It is totally random, not decided in any way.\n\nWhen you toss a coin you 'reject' 50% of of the possible faces, since you can only select either heads or tails. How do you decide which faces to retain and which to reject? The answer of course is that you don't decide, it's pure random chance which one gets rejected and which gets kept. When chromosomes are assorted in meiosis it's pure random chance how they are distributed.\n\n_____________________\n>>>>>Not necessarily rejected. The cells split in two and >>>>>each one has 23 chromosomes. So the other cells are >>>>>used for the next time.\n\nNot in humans, no\n\nIn females the second cell is simply ejected as a polar body and dies. It is rejected in every sense of the word.\n\nAmongst males the second cell will go on to develop onto a spermatozoon simultaneously, nothing 'next time' about it. The odds of both cells being used to fertilise ova would be somewhat less than selecting the right grain of sand out of an entire beach. So for all practical purposes one of those cells will be rejected.
448085
Okay...this may get a little confusing. :) \n\nThe first thing that you need to do is figure out whether the two event listed in each number are independent of each other or dependent.  In this case, the events are dependent.  For example, if you have these 8 marbles in a bag and you pick a green marble out of it...without replacement you would just set that green marble aside.  Now the chances of getting a green or white marble are different because you have changed the total number, does that make sense?\n\nNow, because the events (let's just work with number 1 for example but the same thing can be done to number 2) are dependent, you must use the multiplication rule.  In math terms this says that "The chance that two things both happen equals the chance that the first happens multiplied by the chance that the second happens pretending the first has happened".  In simpler terms this just means that you take the chance that the first will happen and multiply it by the chance that the second thing will happen.  \n\nSo in number 1, the first one you select is a green marble and the second one is a white marble.  The chances of getting the green marble are 3/8 because there are 3 green marbles and 8 marbles all together.  The chances of getting the white marble second are 5/7.  There are 5 white marbles in the bag, but because you have already taken the green marble out you have changed the total number of marbles - hence the 8 in the denominator changes to a 7...does that make sense?\n\nSo your answer to the first one would be (3/8 x 5/7).  I'm not for sure what the numerical answer to that would be, but you can do that calculation on your own! :) \n\nThe second problem can be done the same way, except instead of having a white marble second you would have another green marble.\n\nI really hope that this helps!! :) :) Good luck! :D