Edexcel S3 - Wednesday 25th May AM 2016

Please could anyone explain exercise c question 7a, how do we know that mu=1 by symmetry? Thanks https://771a1ec81340d97ae9ed29694f73dd633b1c7c70.googledrive.com/host/0B1ZiqBksUHNYV1BTbDkxWXZCVmc/CH3.pdf

how are the observed frequencies calculated in this question.

They calculate the $\text{Mean Rate of Accidents} = \dfrac{\text{Total Number of Accidents}}{\text{Total Number of Employees}}$ and use a Poisson distribution to model, as if the null hypothesis is correct this mean is constant and representative of all factories

Sorry I meant to say observed.

When doing the poisson value of say x=0 it yields: 0.0045

But then multiplying it by 15 the answer is 0.0677. and not 21.6 :/

I don't know whether it's possible to draw a table in LaTeX. But if you lay it out it makes complete sense:

$P(X = 0) = 0.4$
$P(X = 1) = 0.2$
$P(X = 2) = 0.4$

If it isn't immediately obvious to you, you can do:

$\displaystyle E(X) = \sum_{i=0}^{2} P(X = i) \times i[br]$

I asked this earlier, I think 15, 15 IAL and 13 R are the difficult ones

Goodness of fit are normally at least 10ish

Sorry I was mistaken with regards to a Poisson model.

The mean rate of accident is in accidents per thousand, so in a thousand employees we would expect 5.4 accidents. So for n thousand employees we would expect 5.4(n) accidents. So for 4 thousand employees we expect 4(5.4) = 21.6 accidents.

thanks that makes sense but on page 79 they multiply the probability by n(80) not the mean.

Quite confusing. Could you clarify this please.

Will examiners mark you down for doing Spearman's and chi-squared working on the given table rather than drawing your own to work on?

do we reckon the paper will be easier than last years?

June 2009, Question 3(c)

Why does the mark scheme answer mean SRCC is better than PMCC? Why does the finishing position need to be normally distributed?




Mark Scheme:

I think they're implictly saying because position isn't normally distributed then you can't use the PMCC since this requires that both variables are normally distributed, so you use SRCC instead, hope that helps

https://771a1ec81340d97ae9ed29694f73dd633b1c7c70.googledrive.com/host/0B1ZiqBksUHNYV1BTbDkxWXZCVmc/CH3.pdf

For question 17 a exercise I why is n=100? Shouldn't it be 200 especially since in part b it is 100?

I assume you're talking about Exercise B, Question 8.

If so, the null hypothesis is referencing the suitability of a Poisson model (this time!) so the procedure to calculate expected values is a little different. We expect 3.45 cells to occur in each square on average but the probability of say 0 cells in the whole population of squares is given by:

$\text{Number of Squares in Total} \times P(X = 0) = 80 \times P(X = 0)$ where $X \sim Po(3.45)$