Term 1 Week 4

Week 4-has been a bit of a recap of what we did in primary school...

Back to square 1...

First of all, we did quite a bit of graph work; relearning how to draw graphs after forgetting everything during our holidays (just joking). We were told that we need to utilise the graph paper as much as possible and not draw one super small graph; to increase the size of each spacing between sections so as to be able to use at least three-quarters of the graph paper. This proved to be quite a challenge for me as sometimes a certain value for each spacing will be just too large and half that would be too small, so I would have to use something in the middle and end up getting decimals for the spacings. This made it even harder to mark the measurements as then I would start to need to in my mind cut up each of the individual squares into smaller parts...I just felt it needed to be precise! (OCD working up) We also had to start from something more than 0 for some graphs-something I found rather difficult as well, as in how to represent it clearly since the graph had two axes. For a graph starting from 0, you just needed to put a 0 at the intersection--but for a graph not starting from 0, the numbers the two axes are starting on are usually different--how do you clearly represent that in such a small space?

We also learnt more about what graphs are and why they are used in the first place instead of charts and tables. Graphs imply a kind of cause and effect relationship, meaning the independent variable (on x, or horizontal, axis) affects the dependent variable (on y, or vertical, axis). Charts and tables are usually just used to display results whereby no relationship between the two variables are established (e.g. fruits secondary school pupils like; you can't have a cause and effect relationship for that!).

Normally, graphs are drawn using either best-fit lines or best-fit curves. Even though a lot of data changes in a linear way, the data points do not usually form a perfect straight line (e.g. you probably won't get 10 deg. Celsius then 20 deg. Celsisus then 30 and so on; you'l probably get something like 11 then 23 then 36 then 45 then 59...), thus a best-fit line is used to get a kind of "average" of the data points; a more linear representation of the data. A best-fit curve, on the other hand, is used when the data is not meant to change linearly/changes linearly up to a certain point before not changing at all (e.g. boiling water), since even though a best-fit line would get roughly the mean, it will be quite far from most of the data points and thus not accurate. Best-fit curves are usually drawn with a flexi-ruler, which is a tool that people use to draw curved lines. (It's quite fun to play with! You should try it!)

The problem about flexi-rulers though is that they sometimes get a bit stiff and deviate from the curve, making the curve rather imperfect. And sometimes you don't know how the curve should look like in between two points, like whether to use a rather gradual curve or instead have a steep drop followed by an almost straight line.

Flexible, useful and sold at only $4.80! (At least at Hwa Chong bookshop)

The next lesson, we learnt about the scientific method (which we also conveniently forgot during the holidays). It consists of the observation, question, hypothesis, method, result and conclusion. This scientific method is a universal process used by scientists around the globe when they do their experiments. Frankly, in my opinion, the result and conclusion are pretty much the same, as well as the observation and question; they are a bit redundant. And the steps for the scientific method are pretty much obvious. What I still don't really understand is, what is the hypothesis for? It is basically a wild guess at what the result will be (if it's not a guess you're probably doing an experiment that your teacher asked you that you already know the answer to-then the experiment is pretty much useless). Some people/worksheets/websites will tell you something like "if your hypothesis is wrong, redo your experiment" or something of that sort. I feel that sometimes making a hypothesis will as a result make you do a biased experiment as you want to get that hypothesis. For example, in primary school, our classmates and I didn't know that friction was not dependent on surface area, so when we did the experiment with the spring balance, we would unconsciously change the amount of force we used as we were not getting the results that we wanted. Some people say that making a hypothesis is so as to have a basis on what you will be answering, but that is answered in the aim, not the hypothesis.