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S1 Help Please.

For question 5(e) of the January 2009 S1 paper, what does it mean by 'average and measure of dispersion'. Why do you choose the median/IQR and how does skewness affect this? Thanks for the help!
(edited 7 years ago)

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Reply 1
Original post by Glavien
For question 5(e) of the January 2009 S1 paper, what does it mean by 'average and measure of dispersion'. Why do you choose the median/IQR and how does skewness affect this? Thanks for the help!


Can you link the paper?
Reply 3


So average is just: which one of mean, mode or median should you use?
Dispersion is just: which one of IQR or range should you use?

Since the data is positively skewed then the mean is unrepresentative of the overall data as it will be skewed positively whereas the median gives you a nice non-skewed 'middle' of the data, i.e: it's not affected by the extreme positive values present because of the skew.

Same goes for range, the range will be exaggerated by the positive skew that makes it much bigger than it should normally thought of to be. SO using IQR cuts out that high-positive end and is a better measure of how the data is dispersed.
Reply 4
Original post by Zacken
So average is just: which one of mean, mode or median should you use?
Dispersion is just: which one of IQR or range should you use?

Since the data is positively skewed then the mean is unrepresentative of the overall data as it will be skewed positively whereas the median gives you a nice non-skewed 'middle' of the data, i.e: it's not affected by the extreme positive values present because of the skew.

Same goes for range, the range will be exaggerated by the positive skew that makes it much bigger than it should normally thought of to be. SO using IQR cuts out that high-positive end and is a better measure of how the data is dispersed.


Thanks so much, that explanation was very helpful!
Reply 5
Original post by Glavien
Thanks so much, that explanation was very helpful!


No problem.
Reply 6
Original post by Zacken
No problem.


Why for question 2(c)(i) of the June 2014 R paper is the probability 0?

Paper: https://1a388b28f5ce9318f837a64962fc3ceab9c61da8.googledrive.com/host/0B1ZiqBksUHNYU2s1SVY1VDN2Q0U/June%202014%20(R)%20QP%20-%20S1%20Edexcel.pdf

Also, for S1 papers what degree of accuracy should you give your answers to?
Reply 7


A continuous distribution has the characteristic that the probability of P(X=anything) = 0 since the probability of picking any single point is 0. When dealing with continuous variables the only times that probabilities are non-zero are when you have intervals, so P(X < 10) or P(5 < X < 7) or w/e. P(X=n) = 0 for all n for a continuous distribution.

Also, for S1 papers what degree of accuracy should you give your answers to?


3 s.f
Reply 8
Original post by Zacken
A continuous distribution has the characteristic that the probability of P(X=anything) = 0 since the probability of picking any single point is 0. When dealing with continuous variables the only times that probabilities are non-zero are when you have intervals, so P(X < 10) or P(5 < X < 7) or w/e. P(X=n) = 0 for all n for a continuous distribution.



3 s.f


Thanks. :smile:
Reply 9
Original post by Glavien
Thanks. :smile:


No problem.
Reply 10
Original post by Zacken
No problem.


Is there any difference in the IAL and UK spec for S1?


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Reply 11
Original post by Glavien
Is there any difference in the IAL and UK spec for S1?


Posted from TSR Mobile


No.
Reply 12
Original post by Zacken
No.


Thanks. Is question 7 of this paper conditional probability. Is an employee owning a bike dependent on them owning a car? How can you tell?

https://1a388b28f5ce9318f837a64962fc3ceab9c61da8.googledrive.com/host/0B1ZiqBksUHNYU2s1SVY1VDN2Q0U/June%202014%20(R)%20QP%20-%20S1%20Edexcel.pdf
(edited 7 years ago)
Reply 13
Original post by Glavien
Thanks. Is question 7 of this paper conditional probability. Is an employee owning a bike dependent on them owning a car? How can you tell?

https://1a388b28f5ce9318f837a64962fc3ceab9c61da8.googledrive.com/host/0B1ZiqBksUHNYU2s1SVY1VDN2Q0U/June%202014%20(R)%20QP%20-%20S1%20Edexcel.pdf


Only part(c) is conditional probability and that is because they use the word "given". In general, dependence has nothing to do with conditional probability.
Reply 14
Original post by Zacken
Only part(c) is conditional probability and that is because they use the word "given". In general, dependence has nothing to do with conditional probability.


So when drawing the tree diagram for the second set of branches, trial 2, should the notation be P(BC)orP(B)P(B|C) or P(B)
Reply 15
Original post by Glavien
So when drawing the tree diagram for the second set of branches, trial 2, should the notation be P(BC)orP(B)P(B|C) or P(B)


The former, but it doesn't really matter.
Reply 16
Original post by Zacken
The former, but it doesn't really matter.


Cool, thanks again. :smile:
Reply 17
Sure.
Reply 18
For question 4(c) of this paper why is it P(L>133L>127)P(L>133|L>127), I don't understand the L>127L>127 bit. I would've thought it would be equal too, but I know that can't be right as then it would be 0 because it is continuous. Also, why isn't it less than?

https://1a388b28f5ce9318f837a64962fc3ceab9c61da8.googledrive.com/host/0B1ZiqBksUHNYU2s1SVY1VDN2Q0U/January%202013%20MA%20-%20S1%20Edexcel.pdf
(edited 7 years ago)
Reply 19
Original post by Glavien
For question 4(c) of this paper why is it P(L>133L>127)P(L>133|L>127), I don't understand the L>127L>127 bit. I would've thought it would be equal too, but I know that can't be right as then it would be 0 because it is continuous. Also, why isn't it less than?

https://1a388b28f5ce9318f837a64962fc3ceab9c61da8.googledrive.com/host/0B1ZiqBksUHNYU2s1SVY1VDN2Q0U/January%202013%20MA%20-%20S1%20Edexcel.pdf


"Given that it is 127 hours since Alice last charged her phone" means that it's been at least 127 hours since Alive charged her phone throughout the journey. So it could be anywhere between 127 hours and infinity hours since she last charged her phone.

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