Science Lab Reflction

Question: What role do multiple observations/experiments play in making good inferences and conclusions in each case?

I feel that it is important to make educated observations in experiments because you can base your inferences and conclusions off of that information. If you don't have the correct information, then you will have incomplete inferences. This will throw off your process of learning, which is not something you want.

Question: When is it hard to be precise and how does this affect the confidence in the results? What did you do about this?

One example of this event was when we were measuring the conductivity of the water. The meter would range from one amount to the next. Finally, we would just have to take the average of the two numbers, but in the end, this might have not been the exact amount. This would matter because it does not make the confidence of the results go up. Instead they would go down. To fix this we tried to get as close as we could to the right answer.

Question: When can you rely on "known" data to match up with and when do you need to generate your own? What's the difference?

I feel that the Bullet Lab was a great example of this. Tanner and I would measure the weight, and type of bullet and try to determine which one it was. We would compare to the slide with all the different types of bullets. This had the "known" data, so to speak. For the fabric Lab, when we were sketching the different samples, we would have to generate our own opinion on what each sample looked like. All the sketches will be different for everyone, but all will have the same overall idea. The difference between known and generated data is that known data is the precise examples whereas generated data is educated data found by yourself.