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    I am doing AQA Stats 1 this year (2016) and I am fine with everything in the module, apart from Conditional Probability. I had a mock exam in January and I got an A but losing nearly all of my marks on Conditional probability questions (apart from the trivial ones). Any tips, help or advice would be great
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    (Original post by JPencil)
    I am doing AQA Stats 1 this year (2016) and I am fine with everything in the module, apart from Conditional Probability. I had a mock exam in January and I got an A but losing nearly all of my marks on Conditional probability questions (apart from the trivial ones). Any tips, help or advice would be great
    Practice as many questions as you can from the textbook, and then look up Solomon questions (if those exist for AQA) or just do whole solomon papers too. Have you got the basic idea of how it works and you get stuck on more complicated things?
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    (Original post by SeanFM)
    Practice as many questions as you can from the textbook, and then look up Solomon questions (if those exist for AQA) or just do whole solomon papers too. Have you got the basic idea of how it works and you get stuck on more complicated things?
    Thanks for the reply. I have done quite a few questions (mostly exam questions) and i keep getting them wrong! I always get the easy questions but I lose nearly all of the marks later in a question I might be something fundamentally wrong but I don't know

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    (Original post by JPencil)
    Thanks for the reply. I have done quite a few questions (mostly exam questions) and i keep getting them wrong! I always get the easy questions but I lose nearly all of the marks later in a question I might be something fundamentally wrong but I don't know

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    It would be useful if you could give some examples of where you are going wrong so we can give you a bit of guidance. The basic idea behind conditional probability is that you simply replace the sample space \Omega with some subset B \subset \Omega that represents a particular event. The all the calculations boil down to diddling with

    \displaystyle P(A|B) = \frac{P(A \cap B)}{P(B)}

    which represents this "reducing" of the sample space from \Omega down to B by a normalization that makes sure that the conditional probabilities add up to one.

    Perhaps the difficulty you're having is in application? When and how to condition on which events? Give us some examples.
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    (Original post by JPencil)
    I am doing AQA Stats 1 this year (2016) and I am fine with everything in the module, apart from Conditional Probability. I had a mock exam in January and I got an A but losing nearly all of my marks on Conditional probability questions (apart from the trivial ones). Any tips, help or advice would be great
    http://www.madasmaths.com/archive/ma...robability.pdf
 
 
 
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