Thursday, May 3, 2007
Trial Number 1!!!
Yesterday I mated my first set of eight females with their first male. There were two irradiation control treatments in which one female was mated with one sterile male. Then the fertile fertile mating was supposed to control for multiply mating a female and not letting the males go to completion. Both the 25/75 and 75/25 splits were used here. Then the more interesting sterile, fertile and fertile, sterile groups were also mated with the same splits listed above. The matings went really well. Today I plan to mate the females with their second males unless they are in the irradiation control group. I also pithed the males that were mated yesterday and put them in the freezer so that I can look at the sperm remaining in their pedipalps and try to get an idea of how much sperm the male had to begin with. So by today I will have 16 less males to feed!! Cruel, huh? But after feeding the spiders each week for 3-5 hours, you get excited when the workload is reduced!!
Statistics Refined
A couple of days ago, Dr. Christenson and I met with Dr. Corey, the psychology statistics guru. We went over the spider design and he thought that it was really sound! He suggested that we do a two way ANOVA looking at the percent of eggs that hatch into spiderlings with the predictor variables being mate order and number of intromissions. I was glad that our control for the irradiation method is adequate even if we mate one female with just one sterile male! This could mean less animals. As far as the multiple egg sacs, Dr. Corey just said to do repeated measures, which was also suggested by Mike. Anyways, I am excited to get this rolling!
Wednesday, April 18, 2007
Multiple Egg Sacs
In breeding the females, I have noticed that they put out multiple egg sacs without having remated. They seem to be able to store sperm for long periods of time after mating with a single male. I am interested to see what sort of role this multiple egg sac laying will play in my manipulation. Will one of the male's sperm be used preferentially over another's? After that male's sperm is used up, will she then use the other's? Is the female able to influence the sperm used to fertilize eggs or does she use whatever is in her storage sac? I should be able to tell when I am able to see whether the percent of eggs hatched changes with each egg sac for the females mated with a sterile male and a fertile male. Maybe the mate order will play a role. This could be pretty interesting! I think I would use MANOVA here?
Friday, April 13, 2007
ANOVA and spiders
When I was going over Chapter 7 in G&E, I had a hard time getting through it because I kept trying to apply everything to my spider study. I even drew in my own little chart next to the one in the book showing a two-way layout in ANOVA. My two factors in this case will be mate order (whether the male is the 1st or 2nd to be mated with the female) and % of intromissions (20,50,80). These are my two categorical predictor variables. My response variable is the percent of eggs hatched. I hope to see a significant response from the % of intromissions, which supports the hypothesis that sperm number determines paternal advantage. I do not expect to see a main effect of mate order. If there was, this would support the hypothesis that the priority pattern is determined by sperm placement, in that the first male is able to place his sperm closer to the fertilization duct and therefore fathers more offspring. I think this will work. If you see any flaws, please feel free to point them out. Also, if I follow the Rule of 10, I will need 10 trial runs or replicates. There are 16 males per replicate (two pairs for sterile, sterile; two pairs for fertile, fertile; two pairs for fertile, sterile; and two pairs for sterile;fertile). The number of intromissions will be varied among the pairs with one being 50/50 and the other 20/80. Total this means I need 160 males!!!
Wednesday, April 11, 2007
Regression
I really liked working through some sample data sets with R on Tuesday. It helped me learned how varying some of the terms could change the coefficent of determination and the p-value. Here is the summary of what I learned:
Regression is used for two continuous variables (both independent and dependent). A regression assumes that there is a cause and effect relationship between x and y. Also, this technique asumes that the x variable is measured without error (can this be done?!?) As far as a linear relationship between two variables, the null hypothesis proposes that there is none and that the slope is 0. The alternative hypothesis depends on slope. Also, the slope, the coefficient of variation, and the sample size all affect the p-value. Remember the p-value is the probability that the slope of the line equals zero and that there is no relationship between variables (null hypothesis).
Regression is used for two continuous variables (both independent and dependent). A regression assumes that there is a cause and effect relationship between x and y. Also, this technique asumes that the x variable is measured without error (can this be done?!?) As far as a linear relationship between two variables, the null hypothesis proposes that there is none and that the slope is 0. The alternative hypothesis depends on slope. Also, the slope, the coefficient of variation, and the sample size all affect the p-value. Remember the p-value is the probability that the slope of the line equals zero and that there is no relationship between variables (null hypothesis).
Thursday, April 5, 2007
ANOVA
Heidi's presentation on Tuesday was very helpful. I especially liked how she covered the assumptions of ANOVA. I also thought that having Thursday's lab also be about ANOVA was well-planned. Though I think that I am getting a good grasp of this test, I think that it is pretty important for us ecology people to truly understand this well. I think that actually doing an ANOVA by hand with a real data set would help to make it more concrete in our minds. Back in ecology lab, this old-fashioned "work out the problem" method helped me to understand t-tests and chi-square tests. I know that it is old school but sometimes using computers does not equal understanding. Anyone of the same opinion?
Spider Update
Sorry it has been so long since my last posting, but I am going to try to make up for it. The good news is that I am finally ready to do a run for my project. I have 16 mature males and 9 mature females ready to go. I am mating them tomorrow! I also will be meeting with my advisor. So I plan to talk about statistical design. As of now, it looks like I will be using ANOVA, ANCOVA, and some t-tests. I am sure this may change as I go along and get a better idea of what I am doing. Also, the males that I am planning to sterilize will have to be placed in a straw using cotton as the stoppers. I took from this class that I should also do this straw cotton treatment for the fertile males as well minus the irradiation of course. Something I am also planning to avoid is confounding my study with time/seasonal issues. Since I can't run all of my runs at once, I plan to have all of my treatment and control groups represented in each run!
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