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Draco's Biology revisionModerator: BioTeam
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Draco's Biology revisionI've started this thread so I can post questions I'm stuck on and my answers to those questions.
I would find it helpful if someone could help me to get the correct answers and even ask me questions from the OCR A level spec. on Human health and disease, Respiration, Photosynthesis, ecosystems, genetics and homeostasis. My first question is: Explain why there is a need for several different diagnostic tests for cystic fibrosis. My answer: Some tests are not reliable by themselves. The best way to check the result is right is to use several tests and take the majority result as the true result. Second question: Could meiosis take place in a triploid (3n) or a tetraloid (4n) cell? Explain your answer. My answer: Meiosis could take place in a tetraloid cell as there is an even number of chromosomes to be divided by two. Thanks to anyone who can help. Why can't this be left blank?
Re: Draco's Biology revisionYour first answer sounds good to me, but as for the second, doesn't the first stage of meiosis double the chromosomes? So why would starting with an even number be necessary?
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Re: Draco's Biology revisionwell, 3X2 = 6
then meiosis produces 4 gametes so 6/4 = bad. Living one day at a time;
Enjoying one moment at a time; Accepting hardships as the pathway to peace; ~Niebuhr
Re: Draco's Biology revisiontrue, that is why triploid plants are always sterile and need to reproduce vegetatively, while tetraploid, hexaploid etc plant can produce seeds
"As a biologist, I firmly believe that when you're dead, you're dead. Except for what you live behind in history. That's the only afterlife" - J. Craig Venter
Ok thanks for that.
I've got another question here. Q: A disease is spreading rapidly through a community. Explain why it is useful to know the incidence and the prevalence of the disease in the community and the mortality from the disease. A: This information about the incidence is useful as it tells how many people are infected so how far spread the disease is, it may also give clues as to how the disease spreads. The prevalence and mortality are also useful to know as this gives information of who is most at risk from the disease and advise can be given to those at risk on how to minimise the chance of catching the disease. If anyone sees any mistakes please let me know. Why can't this be left blank?
Re: Draco's Biology revisionPrevalence is the number (or proportion) of individuals with the disease at any point. It is cumulative; anyone who currently has the disease is counted no matter when they were diagnosed. Incidence is the number (or proportion) of new cases that appear over a specified period, a week for reporting influenza, or a year for cancers, for example. It is not cumulative; someone currently under therapy for a cancer diagnosed in the previous year is not counted in this year’s incidence, but is counted when calculating this year’s prevalence. Prevalence is a measure of how likely you are to ever contract the disease, while incidence is a measure of how likely you are to be diagnosed with the disease over some specified period of time—the next week for flu, or the next year for cancer or schistosomiasis, say. Mortality is the incidence of death due to a disease or condition.
You can figure the chi-squarred stuff out from the link given in the previous reply. Chi-squared is a goodness-of-fit statistic. You know the expected phenotypic ratios, so given a total number of hybrids, you can calculate the expected numbers for each class, and calculate chi-squared statistic for the cross. Each phenotype group will have an associated statistic calculated as (Expected# - Observed#)^2/Expected# and the total chi-squared value is the sum of the individual group chi-squared statistics. This value is then compared to a table of critical chi-squared values for 3 degrees of freedom for a dihybrid cross (#phenotype groups – 1). If the observed chi-squared is less than or equal to the critical chi-squared, then the data is consistent with the expected distribution of phenotypes, otherwise the data are not consistent with the hypothesized distribution. The link Michael gave is OK. Here is one with a worked example. http://waynesword.palomar.edu/lmexer4.htm#chisquare
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