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    IB Math AASL
    /
    Distributions & Random Variables
    /

    Video

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    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.

    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.

    Expected Value

    SL 4.7

    The expected value of a discrete probability distribution is a measure conceptually similar to the mean. It is a weighted sum of all the possible values:

    E(X)=∑x⋅P(X=x)📖


    The expected value is often denoted μ.

    Example

    The probability distribution of X is shown in the following table:

    x

    1

    2

    3

    P(X=x)

    0.1

    0.5

    0.4

    Find E(X).


    E(X)=1⋅0.1+2⋅0.5+3⋅0.4=2.3

    Expected Value

    SL 4.7

    The expected value of a discrete probability distribution is a measure conceptually similar to the mean. It is a weighted sum of all the possible values:

    E(X)=∑x⋅P(X=x)📖


    The expected value is often denoted μ.

    Example

    The probability distribution of X is shown in the following table:

    x

    1

    2

    3

    P(X=x)

    0.1

    0.5

    0.4

    Find E(X).


    E(X)=1⋅0.1+2⋅0.5+3⋅0.4=2.3
    HL