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# Edexcel S3 - Wednesday 25th May AM 2016 watch

1. (Original post by L'Evil Wolf)
Could the conditional probabilitlity/ percentage points/ other S1 stuff be asked in S3.
Yes, although it'd likely to be different to normal conditional probability in that you have to interpret what the condition is, not just use a formula.

An example is in S2, June 2014 about mosquitos if I remember correctly.

And percentage points.. I don't see why they wouldn't

And make sure you can deal with modulus functions as well (e.g. P(mod(x) > 5) for some distribution).
2. (Original post by L'Evil Wolf)
Could the conditional probabilitlity/ percentage points/ other S1 stuff be asked in S3.
Technically yes. Wouldn't really expect it though. Well, conditional probability would be more likely.
3. are there any jan 16 / jan 15 ial papers or anything?

also, do you guys reckon s3 will be harder / easier than last years paper?
4. (Original post by SeanFM)
Yes, although it'd likely to be different to normal conditional probability in that you have to interpret what the condition is, not just use a formula.

An example is in S2, June 2014 about mosquitos if I remember correctly.

And percentage points.. I don't see why they wouldn't

And make sure you can deal with modulus functions as well (e.g. P(mod(x) > 5) for some distribution).
Thank you, yes I have done those types, thnx for your help.

(Original post by 13 1 20 8 42)
Technically yes. Wouldn't really expect it though. Well, conditional probability would be more likely.
I see. Thank you.
(Original post by tazza ma razza)
are there any jan 16 / jan 15 ial papers or anything?

also, do you guys reckon s3 will be harder / easier than last years paper?
(Original post by tazza ma razza)
are there any jan 16 / jan 15 ial papers or anything?

also, do you guys reckon s3 will be harder / easier than last years paper?
No only june papers.

Can't tell, email edexcel :P
5. https://869d950bf149eefd5cd2652b4001...%20Edexcel.pdf

For question 8b when it is a fraction, do you still square the variance?
6. (Original post by L'Evil Wolf)
https://869d950bf149eefd5cd2652b4001...%20Edexcel.pdf

For question 8b when it is a fraction, do you still square the variance?
Yeah
edit: Well actually I'm not quite sure what you mean. When finding the variance of C - 4/5D you do Var(c) + (4/5)^2Var(D) if that's it
7. (Original post by 13 1 20 8 42)
Yeah
Is there a reason why please? If it was 1 instead of the fraction then no squaring - right?

part b is ridiculous that is d1 inequalities wtf
8. (Original post by L'Evil Wolf)
Is there a reason why please? If it was 1 instead of the fraction then no squaring - right?

part b is ridiculous that is d1 inequalities wtf
I've edited my post above to check you mean what I think you mean...if that's the case then the thing is 1 = 1^2 so you are still squaring
9. (Original post by 13 1 20 8 42)
Yeah
edit: Well actually I'm not quite sure what you mean. When finding the variance of C - 4/5D you do Var(c) + (4/5)^2Var(D) if that's it
I don't get how you square, if it is not independent?
10. (Original post by L'Evil Wolf)
I don't get how you square, if it is not independent?
Well C and D are independent variables?
11. (Original post by 13 1 20 8 42)
Well C and D are independent variables?
Thank you.
12. https://771a1ec81340d97ae9ed29694f73...XZCVmc/CH3.pdf

Can smoeone explain EXB Q6 b and c please, where does p come about and how to work out the final part.
13. do you have to show youre working out when doing sigma X^2 etc
14. (Original post by L'Evil Wolf)
https://771a1ec81340d97ae9ed29694f73...XZCVmc/CH3.pdf

Can smoeone explain EXB Q6 b and c please, where does p come about and how to work out the final part.
Definition of bias of an estimator, eg the estimator xbar, is E(Xbar) - parameter that is being estimated.

In your textbook you'll probably have seen it as E(theta) - theta. So you are told in the question that you are trying to estimate p with the estimator xbar, so the bias is E(xbar) - p, and the unbiased estimator is the one required for E(f(xbar)) - p = 0 where f is some function of xbar (in this case, you divide it by 10 since E(xbar) = 10p, so E(xbar/10) = 1/10 E(xbar) = 10/10 p = p, and then p-p=0 so xbar/10 is unbiased.
15. So when would we test for H1: p<0 for spearmans rank (apart from a standard q where it is asking if there is disagreement)? Like testing someone's claim would it be likely that it is mostly p>0 or p not equal to 0?

Also could we be asked q's involving pdfs and cdfs from s2? Maybe even having to use clt on it?
16. (Original post by SeanFM)
Definition of bias of an estimator, eg the estimator xbar, is E(Xbar) - parameter that is being estimated.

In your textbook you'll probably have seen it as E(theta) - theta. So you are told in the question that you are trying to estimate p with the estimator xbar, so the bias is E(xbar) - p, and the unbiased estimator is the one required for E(f(xbar)) - p = 0 where f is some function of xbar (in this case, you divide it by 10 since E(xbar) = 10p, so E(xbar/10) = 1/10 E(xbar) = 10/10 p = p, and then p-p=0 so xbar/10 is unbiased.
Thank you sean
17. (Original post by Rkai01)
So when would we test for H1: p<0 for spearmans rank (apart from a standard q where it is asking if there is disagreement)? Like testing someone's claim would it be likely that it is mostly p>0 or p not equal to 0?

Also could we be asked q's involving pdfs and cdfs from s2? Maybe even having to use clt on it?
no test generally refers to 2 tailed test

18. If rankings are tied in spearmans rank say at 5 there are two values which are equal then would we give it a value of 5.5, I tried doing this for a question but the difference, d was not equal to 0.
19. (Original post by L'Evil Wolf)
If rankings are tied in spearmans rank say at 5 there are two values which are equal then would we give it a value of 5.5, I tried doing this for a question but the difference, d was not equal to 0.
My knowledge of spearmans is a bit rusty, but does the difference have to be 0? And that, in the case of tied ranks, you can use something else?
20. If you work out the expected values for a contingency table in a goodness of fit question and get fractions, do you round it up before working out chi squared??

I was doing a solomon paper just now and in the mark scheme they rounded up their expected values to 2dp so my answer was about 0.002 away from their answer. Do you know if I'd lose the mark if I did that in the real thing?

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