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# Edexcel S2 - 27th June 2016 AM Watch

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1. (Original post by Ayman!)
X <k/2 means that X < k, so we can just write it as X < k/2.
What is this??? like what topic
2. (Original post by SSD07)
What is this??? like what topic
Conditional probability applied to continuous distributions. Quite common as of late in stats papers - came up in my S3
3. Hi there, im stuck with this question, where for part a)i & a)ii i can't figure out how to hack the alternative method (2), especially for a)ii where for X~B(10,0.4) shouldn't P(X<9) be equivalent to P(x<=1). Plus for part b im lost. thanks in advance
Attached Images

4. (Original post by taysc)
Does anyone have a good way/acronym of remembering skewness in terms of mode median and mean?

Im struggling to remember the pattern
I don't have an acronym to help but for some reason drawing these graphs help. Mode is always the 'peak' or most dense part of the PDF so draw that in, then draw in the median and/or mean depending on it's value being greater or less than the mode. If the PDF you draw is more dense towards the vertical axis (i.e. the mode is closest to the vertical), it is positive skew, and vice-versa. This helped me, maybe I just have an odd way of learning things.

5. S2 June 2011. Need help with question 6b please. Can anyone tell me if/why my working is incorrect?

In the mark scheme they go with working from this approach, but is the opposite true too? I worked from:

My full working and question below:
Attached Images

6. (Original post by yuveethini)
Hi there, im stuck with this question, where for part a)i & a)ii i can't figure out how to hack the alternative method (2), especially for a)ii where for X~B(10,0.4) shouldn't P(X<9) be equivalent to P(x<=1). Plus for part b im lost. thanks in advance
Think of it like this - if you flipped a coin 10 times, and you wanted to model how many times you get a head, say X is the distribution of number of heads and X~B(n,p) then you can also measure it with another distribution, Y, the number of tails. Y~(n,1-p). Why are the probabilities that way? Because if p is the probability of getting a heads, 1-p is the probability of getting a tails.

Now, X = 6 is the same as saying Y = 4. If you read that in English, it's the same as saying getting 6 heads is the same as getting 4 tails. So the distributions might be different, but they're modelling the same outcome (6 heads and 4 tails) and the water example is doing the same thing.

For part aii, the RHS, you may have missed out how they're using X and Y instead of just X. Saying X (the number of customers who order water, and Y is the number who don't) - you say that the probability of strictly less than 9 customers ordering water is the same as the probability of strictly more than 1 customer ordering water, and the probability of that is 1 - p(less than or equal to 1 customer not ordering water).
S2 June 2011. Need help with question 6b please. Can anyone tell me if/why my working is incorrect?

In the mark scheme they go with working from this approach, but is the opposite true too? I worked from:

My full working and question below:
The statements are pretty much equivalent (I'm not 100% sure about the first inequality sign in your second line of latex, it may have to be strictly less than 31 but I'm not sure) so I suppose you could work like that, though it'd be a bit strange.
8. (Original post by SSD07)
What is this??? like what topic
Look at it this way - if I told you that BOTH X<10 and X<5 (what the intersect is basically), then which inequality implies the other?

X<10 doesn't imply that X<5, because X could be 6,7,8,9 so the first one would be true but the second not.

But X<5 implies that X<10 - if the first one is true, the second one is, so that's why the intersection of the two is X<5.

Similarly, if you had Y> 7 and Y > 11 - the second one implies the first, but not the other way round, so the intersection would be Y > 11.
9. (Original post by SeanFM)
The statements are pretty much equivalent (I'm not 100% sure about the first inequality sign in your second line of latex, it may have to be strictly less than 31 but I'm not sure) so I suppose you could work like that, though it'd be a bit strange.
Thank you! It's a normal approximation so I don't think it matters whether it's a strict inequality or not. Doing it this way just means that I can work from tables straight away, without having to do 1 - probability later on. I guess I should just stick with the mark scheme method.
10. https://57a324a1a586c5508d2813730734...%20Edexcel.pdf

can someone help me with question 8

why did they e^-2x/15. like i dont get where the exponential came from but i get the 2x/15.

https://57a324a1a586c5508d2813730734...%20Edexcel.pdf
Thank you! It's a normal approximation so I don't think it matters whether it's a strict inequality or not. Doing it this way just means that I can work from tables straight away, without having to do 1 - probability later on. I guess I should just stick with the mark scheme method.
I see what you're saying, but both regions include the critical value (which is what matter, you're right with the rest and like 30.9999999 and all of that) and I'm not sure if, by definition, it should be inclusive if you're going to do it that way - maybe I am just making things up ) but fair enough - personally, if you got it right that way I'd give you the marks but.. better safe than sorry, I s'pose
12. (Original post by SeanFM)
I see what you're saying, but both regions include the critical value (which is what matter, you're right with the rest and like 30.9999999 and all of that) and I'm not sure if, by definition, it should be inclusive if you're going to do it that way - maybe I am just making things up ) but fair enough - personally, if you got it right that way I'd give you the marks but.. better safe than sorry, I s'pose
I get you haha, my teacher used to say "You're arguing about the area of a line" for any probability of an exact value when the variable is continuous, but you are definitely correct. I'll just hope that a normal approximation and hypothesis test don't come up in the same question this year! Cheers dude.
13. the grade boundaries are so high wtf
14. (Original post by Lilly1234567890)

can someone help me with question 8

why did they e^-2x/15. like i dont get where the exponential came from but i get the 2x/15.
The exponential comes from the Poisson Distribution probability function in the formula booklet:

Where as a result of the question, this becomes:

Then just sub in 1.65 and 1.75 giving values either side of 0.8, therefore showing that x=1.7 as required.
The exponential comes from the Poisson Distribution probability function in the formula booklet:

Where as a result of the question, this becomes:

Then just sub in 1.65 and 1.75 giving values either side of 0.8, therefore showing that x=1.7 as required.
thanks !
16. Help with this question please

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17. i have always known that if our value is less than 0.05. ten there is sufficient evidence to reject H0. But that doesnt seem to be the case here in q5

https://57a324a1a586c5508d2813730734...%20Edexcel.pdf

is the mark scheme wrong

https://57a324a1a586c5508d2813730734...%20Edexcel.pdf
I don't have an acronym to help but for some reason drawing these graphs help. Mode is always the 'peak' or most dense part of the PDF so draw that in, then draw in the median and/or mean depending on it's value being greater or less than the mode. If the PDF you draw is more dense towards the vertical axis (i.e. the mode is closest to the vertical), it is positive skew, and vice-versa. This helped me, maybe I just have an odd way of learning things.

This really helpful, I'm going to try it today with the last papers that I do.

Thank you
19. (Original post by SeanFM)
Think of it like this - if you flipped a coin 10 times, and you wanted to model how many times you get a head, say X is the distribution of number of heads and X~B(n,p) then you can also measure it with another distribution, Y, the number of tails. Y~(n,1-p). Why are the probabilities that way? Because if p is the probability of getting a heads, 1-p is the probability of getting a tails.

Now, X = 6 is the same as saying Y = 4. If you read that in English, it's the same as saying getting 6 heads is the same as getting 4 tails. So the distributions might be different, but they're modelling the same outcome (6 heads and 4 tails) and the water example is doing the same thing.

For part aii, the RHS, you may have missed out how they're using X and Y instead of just X. Saying X (the number of customers who order water, and Y is the number who don't) - you say that the probability of strictly less than 9 customers ordering water is the same as the probability of strictly more than 1 customer ordering water, and the probability of that is 1 - p(less than or equal to 1 customer not ordering water).
Ohhhh i get it now thank you
Also how do i go about doing part b, i just dont understand it
20. (Original post by SeanFM)
Number of correct answers = X. number of incorrect answers = 20 - X.

number of points from total correct answers = ...

number of points docked from total incorrect answers = ...

hence...

it's not asking for you to find that it's when you get 4 correct answers and 16 incorrect answers (which doesn't quite make sense, though I see what you are trying to do)

It's asking how many points you get when X answers are right. (implying that 20-X are wrong).
thanks bro

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