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    IB Math AASL
    /
    Descriptive Statistics
    /

    Video

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    Watch comprehensive video reviews for most units, designed for final exam preparation. Each video includes integrated problems you can solve alongside detailed solutions.

    Not your average video:

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    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.

    Descriptive Statistics

    Video Reviews

    Watch comprehensive video reviews for Descriptive Statistics, 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.

    Data & SamplesMeasuresVisualsRegression

    The video will automatically pause when it reaches a problem.

    Pearson's Product-Moment Correlation Coefficient

    SL 4.4

    Pearson's product-moment correlation coefficient, denoted by r, measures the strength and direction of a linear relationship between two numerical variables x and y. Its value always lies between −1 and +1:

    • r=+1: perfect positive linear relationship

    • r=−1: perfect negative linear relationship

    • r=0: no linear relationship

    A positive value means y generally increases as x increases; a negative value means y generally decreases as x increases. The closer r is to ±1, the stronger the linear relationship.


    Pearson’s coefficient is calculated by:

    r=√∑(x−xˉ)2∑(y−yˉ​)2​∑(x−xˉ)(y−yˉ​)​

    Note: you do not need to use or know this formula.


    On exams, r is determined using technology.


    Example 1

    Find r for the following data, and interpret its significance.

    x

    3

    4

    5

    6

    y

    −8

    −12

    −16

    −17

    Using a calculator, we find r=−0.973. This indicates a very strong, negative relationship.

    Powered by Desmos


    Example 2

    Find r for the following data, and interpret its significance.

    x

    3

    4

    5

    6

    y

    −8

    12

    −16

    5

    Using a calculator, we find r=0.11. This indicates essentially a weak positive relationship, but there is almost no correlation.

    Powered by Desmos

    Pearson's Product-Moment Correlation Coefficient

    SL 4.4

    Pearson's product-moment correlation coefficient, denoted by r, measures the strength and direction of a linear relationship between two numerical variables x and y. Its value always lies between −1 and +1:

    • r=+1: perfect positive linear relationship

    • r=−1: perfect negative linear relationship

    • r=0: no linear relationship

    A positive value means y generally increases as x increases; a negative value means y generally decreases as x increases. The closer r is to ±1, the stronger the linear relationship.


    Pearson’s coefficient is calculated by:

    r=√∑(x−xˉ)2∑(y−yˉ​)2​∑(x−xˉ)(y−yˉ​)​

    Note: you do not need to use or know this formula.


    On exams, r is determined using technology.


    Example 1

    Find r for the following data, and interpret its significance.

    x

    3

    4

    5

    6

    y

    −8

    −12

    −16

    −17

    Using a calculator, we find r=−0.973. This indicates a very strong, negative relationship.

    Powered by Desmos


    Example 2

    Find r for the following data, and interpret its significance.

    x

    3

    4

    5

    6

    y

    −8

    12

    −16

    5

    Using a calculator, we find r=0.11. This indicates essentially a weak positive relationship, but there is almost no correlation.

    Powered by Desmos

    Data & SamplesMeasuresVisualsRegression