1. What role do multiple observations/experiments play in making good inferences and conclusions in each case?
This is sort of the same question as the one from the blood splatter lab, but I'll do the best I can to answer it in different words. :)
Having multiple trials or samples, helps make better conclusions because there is more data to look at. For example in the fibers lab we had three different magnifications for each of the samples AND we had the data from burning the fiber to compare to the fiber from the victim. It was similar for the other two labs, for each sample there were multiple tests to compare to. In the soil lab we did the water absorbency, the pH level, and the conductivity test. In the bullet lab we looked at the shell casing, the bullet and record the weight, imprint, and other observations about how the bullet looked.
2. When is it hard to be precise and how does this affect the confidence in your results? What did you do about this?
I think that in each lab, there is always a time when it is impossible to be completely accurate, and when it doesn't matter too much if the answers aren't completely correct, because it is about the proccess not the product. For example, in the soil lab, we would aproximate the pH level, because it didn't matter if the decimemal was one or two tenths off. In the bullets lab, it was sometimes easy to be accurate. The grams/grains were clear, and involved calculations to get the answers. But it was hard to be exactly precise with measurements, especially while measuring lands/groves and diameter. Also, there were times when our information didn't match up with the data tables and sheets that were provided, and we had to estimate a little or round up numbers. In the fibers lab it was hard to be accurate in data, sometimes our samples would be different sizes or lengths so it was hard to compare to the victim sample while burning them. Being less accurate definetly affected the confidence in my results. When we "fudged" the answers a little bit, OUR data might not match up with the data from the bullet refrence sheet, or even other samples. I don't think there is much you can do about this, except to try to be accurate and aproximate the answers.
3. When can you rely on "known" data to match up with and when you need to generate your own? What is the difference?
"known" data is information that you already have, or information that has been given to you and you have to generate information by looking at the samples, running tests and making your own hypothesis about who the victim was. In all three labs, there was known data provided and parts where you had to generate your own. In the bullets lab, the known data was the powerpoint, it gave examples and information on how to identify different parts of a gun and bullet. The data you had to generate was examining the bullets and recording the information like weight, bullet type, lands and groves, etc. In the fibers lab, the known data was the sample from the victim, and the other samples because you already had them, and the information about which person each sample came from. The data you had to generate was looking through the microscope and recording what you saw and burning the fibers and recording that information as well. In the soil lab, the known data was where the dirt samples came from and the data you had to gather was the pH levels, water absorbency, and conductivity test.
Good job accounting for multiple ways of looking at evidence across all three labs. You might also consider that comparing evidence from multiple suspects or samples itself provides another form of making multiple observations and allows for doing the comparison with evidence from a crime scene. You also make solid distinctions about the source of possible error in your observations and good assessments of how sound your conclusions can be as a result. Lastly, you make an accurate distinction about the role of known data in comparing evidence versus having to generate your own data.
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