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    IB Math AASL
    /
    Distributions & Random Variables
    /

    Video

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    Not your average video:

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    Expert Teaching: High-quality instruction from Perplex co-founder James Mullen with clear explanations, worked examples, and exam tips.

    Distributions & Random Variables

    Video Reviews

    Watch comprehensive video reviews for Distributions & Random Variables, designed for final exam preparation. Each video includes integrated problems you can solve alongside detailed solutions.

    Not your average video:

    Interactive Problems: Solve problems alongside the video with step-by-step guidance and detailed solutions.

    Exam Preparation: Complete unit reviews designed for final exam preparation with all key concepts covered systematically.

    Expert Teaching: High-quality instruction from Perplex co-founder James Mullen with clear explanations, worked examples, and exam tips.

    Not your average video:

    Interactive Problems: Solve problems alongside the video with step-by-step guidance and detailed solutions.

    Exam Preparation: Complete unit reviews designed for final exam preparation with all key concepts covered systematically.

    Expert Teaching: High-quality instruction from Perplex co-founder James Mullen with clear explanations, worked examples, and exam tips.

    HL

    The video will automatically pause when it reaches a problem.

    Discrete probability expressions

    SL 4.7

    Probability distributions can also take the form

    P(X=x)=(expression in x),x∈{set of possible x}


    For example:

    P(X=x)=221​(3x−2),x∈{1,2,3,4}


    Notice that

    221​[(3−2)+(6−2)+(9−2)+(12−2)]=2222​=1


    This is not a coincidence, the 221​ was specifically chosen so that the probabilities would sum to 1.


    Example

    Find the value of k in the probability distribution

    P(X=x)=k(x+2),x∈{1,2,3}.


    Plugging in each of values of x and adding the probabilities:

    k[(1+2)+(2+2)++(3+2)]=12k=1

    so k=121​.

    Discrete probability expressions

    SL 4.7

    Probability distributions can also take the form

    P(X=x)=(expression in x),x∈{set of possible x}


    For example:

    P(X=x)=221​(3x−2),x∈{1,2,3,4}


    Notice that

    221​[(3−2)+(6−2)+(9−2)+(12−2)]=2222​=1


    This is not a coincidence, the 221​ was specifically chosen so that the probabilities would sum to 1.


    Example

    Find the value of k in the probability distribution

    P(X=x)=k(x+2),x∈{1,2,3}.


    Plugging in each of values of x and adding the probabilities:

    k[(1+2)+(2+2)++(3+2)]=12k=1

    so k=121​.

    HL