VCE General & Further Maths Question Thread!

[AngelWings]

How about cutting at the red line?

Should be just as fine. Might make it a little harder to read some of the notes beside the red line when bound, but whatever floats your boat.

hey
i am stuck on the attached questions, any help will be appreciated.....

thanks!

Looks like Hungry4Apples has you covered for this!

[MightyBeh]

Hey there,
if I write out the coefficient of determination (r^2) as both a decimal and a percentage, is that okay?
I did so in my SAC today, and I'm feeling very anxious as to whether I lost a mark for that or not.
Thanks!

Could you give an example? It sounds like it's fine though. If it's something along the lines of 'the coefficient of determination of 0.9284 (92.84%) indicates that ...', I can't imagine you'd lose marks.

[drepwns]

Could you give an example? It sounds like it's fine though. If it's something along the lines of 'the coefficient of determination of 0.9284 (92.84%) indicates that ...', I can't imagine you'd lose marks.

If I can remember clearly, the question asked to specify the coefficient of determination, and then interpret it. What I did was write out 'coefficient of determination = 0.642 or 64.2% and then in the next line, I interpreted it using 'the coefficient of determination of 64.2% indicates that...'

[MightyBeh]

If I can remember clearly, the question asked to specify the coefficient of determination, and then interpret it. What I did was write out 'coefficient of determination = 0.642 or 64.2% and then in the next line, I interpreted it using 'the coefficient of determination of 64.2% indicates that...'

That's perfectly fine! You should get full marks for that.

[Hungry4Apples]

Hello again,
so today in my SAC - I used both the correlation coefficient and the residual plot to suggest the superior predictive model.
I recognise that using the coefficient of determination is the right way, but yet again - the pressure under SAC conditions eats away at me.
Is using the correlation coefficient alright, or was I meant to use the coefficient of determination? Thanks.

From memory the coefficient of determination is used to determine how much of the variation in the dependant variable can be explained by the variation in the independent variable. I'm pretty sure that the correlation coefficient is used to determine how strong the linear relationship is so I think you should be safe.

[Mariamnourine]

Hey everyone!!!

I did my first SAC and got a 70/80 (88%) . I was rank 4 ans was quite surprised with my score (and rank!) as I had not done the last chapter in time for my SAC
However I was curious, can someone tell me their SAC marks and exam marks- ans what overall study score did you get?

[TheCommando]

Hey everyone!!!

I did my first SAC and got a 70/80 (88%) . I was rank 4 ans was quite surprised with my score (and rank!) as I had not done the last chapter in time for my SAC
However I was curious, can someone tell me their SAC marks and exam marks- ans what overall study score did you get?

Its ultimately your exam scores that determind your study scores. I've heard alot of people getting good or bad study scored only to get completley different study scores to what they got in their ss

[pmmenotes]

What do I say for 'Which prediction from part d and c is more reliable ?

is it related to intra/extrapolation.

[TheCommando]

What do I say for 'Which prediction from part d and c is more reliable ?

is it related to intra/extrapolation.

No, its rekated to the r value which is the correlatin coeffection. A higher r value means its more accurate. The correlation coefficient is a measurement of the strength of a linear relationship which is the x and y axis.

Interpolation and expolation is used to determing weather a data would be considered accurate or not, as iterpolation is predicting values within a data set which means it would be reliable however if its predicts outside a dataset its not accurate and therefore is expolation

[pmmenotes]

Can someone help me with this ASAP 
Really dont get it

"In 1990 18.4% of the population in Belarus were obese whereas in 2010 17.1% of the population were obese. Calculate and interpret the residual value when the least square regression line is used to predict the 2010 from 1990. Round to 1 decimal place.

- Have the 1990 and 2010 data sets on my calc

HOW WOULD I GO ABOUT ANSWERSING THIS I DONT GET WHAT IT MEANS???

'interpret the vertical intercept of least square regression line in terms of variables 1990 and 2010"
i have the data for 2010 on 1990 on my calc

Mod Edit [Aaron]: Posts merged. Double posting unjustified.

[TheCommando]

Can someone help me with this ASAP 
Really dont get it

"In 1990 18.4% of the population in Belarus were obese whereas in 2010 17.1% of the population were obese. Calculate and interpret the residual value when the least square regression line is used to predict the 2010 from 1990. Round to 1 decimal place.

- Have the 1990 and 2010 data sets on my calc

residual value is the original value - predicted value
In this case the original value is 17.1 since its the orginal value as its stated that the rate is 17.1% in your question
The precdicted value is simply the value when u plug 18.4%'in your regression line
Then just put thoose two vales in the residual equation and you should get the answer

Ps a residual measures the distance between the regression line and the actual corodinates on the graph

[Maya24]

Can someone help me with this ASAP 
Really dont get it

"In 1990 18.4% of the population in Belarus were obese whereas in 2010 17.1% of the population were obese. Calculate and interpret the residual value when the least square regression line is used to predict the 2010 from 1990. Round to 1 decimal place.

- Have the 1990 and 2010 data sets on my calc

HOW WOULD I GO ABOUT ANSWERSING THIS I DONT GET WHAT IT MEANS???

'interpret the vertical intercept of least square regression line in terms of variables 1990 and 2010"
i have the data for 2010 on 1990 on my calc

Mod Edit [Aaron]: Posts merged. Double posting unjustified.

I had this exact same question on my sac.
so you do
17.1%-(8.1+0.93*18.4%)
=-8.112x-8.1

[pmmenotes]

I had this exact same question on my sac.
so you do
17.1%-(8.1+0.93*18.4%)
=-8.112x-8.1

Thank you so much legit lifesaver! dont know of this is too much of a ask but im so lost, what would you say for the interpt part of the question
? thanks again all good if you can't answer xxxx

[TheCommando]

Can someone help me with this ASAP 
Really dont get it

"In 1990 18.4% of the population in Belarus were obese whereas in 2010 17.1% of the population were obese. Calculate and interpret the residual value when the least square regression line is used to predict the 2010 from 1990. Round to 1 decimal place.

- Have the 1990 and 2010 data sets on my calc

HOW WOULD I GO ABOUT ANSWERSING THIS I DONT GET WHAT IT MEANS???

'interpret the vertical intercept of least square regression line in terms of variables 1990 and 2010"
i have the data for 2010 on 1990 on my calc

Mod Edit [Aaron]: Posts merged. Double posting unjustified.

The vertical intercept estimates the average vlaue of the response variable when the explanatory variable equals 0

since you wish to predict the obesity rate in 2010 this is your response rate
Since the obesity rate in 1990 is used to predit the rate of obesity in 2010 this is your explanatory variable

For eg, if rate of obesity in 2010= 7.8 x rate of obesity in 1990 +70
You would just say
The intercept estimates the rate of obesity in 2019 will be 70 when the rate of obesity in 1990 is 0
Just simply locate the 70 and say thats the predicted response variable when the explanatory variable is 0. Of course u have to say what the resonse and explanatory variable is

[pmmenotes]

I had this exact same question on my sac.
so you do
17.1%-(8.1+0.93*18.4%)
=-8.112x-8.1

Also where  did you get the 8.1+0.93 bit?
my least sq regression line equation was y=6.24+0.993x
with y being twentyten and x being 1990