June 07, 2023, 02:43:41 am

### AuthorTopic: VCE General & Further Maths Question Thread!  (Read 685188 times) Tweet Share

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#### Billuminati

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##### Re: VCE General & Further Maths Question Thread!
« Reply #2730 on: July 05, 2022, 02:20:41 pm »
+1
Graphs and relations question:
In the exam does it matter if you don't use the formula (y-y1)=m(x-x1)?
As I would prefer to work with y=mx+c but don't want to be losing marks if the other is necessary for the exam working out.
Thanks

I never had to use the first form. FM exams always ask questions in the gradient intercept form ie the y = mx + c one since they want you to interpret m and c in the context of the question
VCE 2016-2018

2017: Biology [38], Further Maths [44]

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#### valjaybj

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##### Re: VCE General & Further Maths Question Thread!
« Reply #2731 on: July 05, 2022, 09:44:28 pm »
0
G'day,

I am a tutor in Further Mathematics, but have a question for fellow experts and students.

The picture attached is of a question my student attempted. The content is on chapter 3 of cambridge, so is on least squares regression. A few issues:

- The original data has a massive outlier, so shouldn't even be subject to least squares regression per the assumptions

- The picture is of the residual plot, which to me has no real observable pattern given the outlier, however perhaps the definition of "pattern" is not so clear cut? I imagine the pattern being non-linear or curved or some such, so how do we distinguish between pattern and non pattern?

Thanks for the help. Hopefully someone more zen than I can help me understand why we'd approach this question despite the outlier being present!

Cheers

hi! this is quite a late reply haha but i think that's what they're actually asking for in terms of why a regression analysis is not appropriate for the data. like you said there's a very clear outlier, and also there seems to be a decreasing pattern and somewhat linearity in the rest of the residual plot. ofc a pattern in the residual plot indicates the data is non-linear and hence further supports why linear regression is not suitable for the data. i feel like you just have to go with the information they've provided and then use your observations to answer part g