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    2016 predicted paper online check it out


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    (Original post by Usmaan345)
    2016 predicted paper online check it out


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    Hi, Where about's is this paper?
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    (Original post by Nikhilm)
    Any hard non-edexcel papers? Zacken
    Dunno, haven't done anything other than edexcel papers.
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    (Original post by Zacken)
    Dunno, haven't done anything other than edexcel papers.
    Zacken is chapter 3 Ex 17 in the book wrong, the tails look double what they should be..
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    (Original post by Usmaan345)
    2016 predicted paper online check it out


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    Thats it were sorted, 100% sorted. Cmon lads


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    (Original post by L'Evil Wolf)
    Zacken is chapter 3 Ex 17 in the book wrong, the tails look double what they should be..
    Seems fine to me.
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    (Original post by Zacken)
    Seems fine to me.
    Yes it is oops.

    Is the formula of the confidence levels:

    (1 - 2*area each side of the tail) * 100%
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    For q6b on this paper, can someone tell me why mention of the normal distribution doesn't score the mark? it's a valid assumption?

    Paper: https://869d950bf149eefd5cd2652b4001...%20Edexcel.pdf
    MS:https://869d950bf149eefd5cd2652b4001...%20Edexcel.pdf



    Zacken
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    (Original post by Katiee224)
    For q6b on this paper, can someone tell me why mention of the normal distribution doesn't score the mark? it's a valid assumption?

    The CLT is not an assumption, it's a theorem.
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    (Original post by Zacken)
    The CLT is not an assumption, it's a theorem.
    ohh i miss understood the question, thanks zacky
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    (Original post by L'Evil Wolf)
    Yes it is oops.

    Is the formula of the confidence levels:

    (1 - 2*area each side of the tail) * 100%
    Yeh you get the percentage 1- it and half it and look in the samll P(Z>z) tables at the back. Then do
    x+-numbers(sd/sqrtn)


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    What is going on in the variance part of the attached example? I cannot for the life of me understand where this 29 is coming from...
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    (Original post by paradoxequation)
    What is going on in the variance part of the attached example? I cannot for the life of me understand where this 29 is coming from...
    Because the value of n is 30, the value on the denominator is n-1 for unbiased estimators of the variance so 30-1=29, hope that helps
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    Quick question, if we get tied ranks when calculating spearmans rank correlation coefficient, are we meant to abandon it and use the pmcc instead?

    Does anyone know what we're meant to do
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    (Original post by paradoxequation)
    What is going on in the variance part of the attached example? I cannot for the life of me understand where this 29 is coming from...
    they used the formula for the unbiased variance where the 29 comes from (n-1) with n=30
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    (Original post by Katiee224)
    they used the formula for the unbiased variance where the 29 comes from (n-1) with n=30
    (Original post by economicss)
    Because the value of n is 30, the value on the denominator is n-1 for unbiased estimators of the variance so 30-1=29, hope that helps
    Yh thanks guys! Completely glossed over that formula, didn't know it was a standard one.
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    (Original post by paradoxequation)
    What is going on in the variance part of the attached example? I cannot for the life of me understand where this 29 is coming from...
    I understand, i didnt see that formula a few weeks ago and was like wtf is going on.


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    (Original post by Zacken)
    The CLT is not an assumption, it's a theorem.
    So if a question asks what assumptions have been made, am I right in thinking it could never be that we've assumed the population is normally distributed with the central limit theorem? Not sure on my wording there, thanks
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    (Original post by economicss)
    So if a question asks what assumptions have been made, am I right in thinking it could never be that we've assumed the population is normally distributed with the central limit theorem? Not sure on my wording there, thanks
    We assume that the unbiased variabce equals variance.


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    Did anyone do UK May 15 and think it was a nice paper?
 
 
 
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