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    IB Math AAHL
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    Descriptive Statistics
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    Descriptive Statistics

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    IB: 4
    1

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    The sum of the 13 elements of set S is 104.

    1. Write down the mean of S.

      [1]

    The set G is formed by doubling each element of S and adding 1.

    1. Find the mean of G.

      [1]

    It is given that the variance of G is 36.

    1. Find the standard deviation of S.

      [3]
    2

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    At the end of the 2024 fishing season on Fork Lake, 60 anglers (amateur fishers) were randomly surveyed. They were asked how many bass they caught over the whole season. The information is summarized in the following frequency table:

    Number of fish caught

    Frequency

    0

    7

    1

    12

    2

    10

    3

    19

    4

    k

    5

    3

    Assume that this sample is representative of all anglers in any season, and that all anglers have equal skill.

    1. State the value of k.

      [1]
    2. For the 2025 season estimate

      1. the probability a randomly selected angler will catch fish,

        [1]
      2. the expected number of fish caught by an angler over the season.

        [2]

    The U.S Fish and Wildlife Service (USFWS) estimates that the bass population in Lake Fork will grow by 8% between the 2024 and 2025 fishing seasons.

    1. Given that the bass population was 110′000 at the end of the 2024 season, estimate the number of bass in the Lake at the opening of the 2025 season.

      [1]

    The USFWS wants the bass population to remain unchanged year to year.

    1. How many seasonal fishing permits should be granted in 2025? Give your answer to the nearest hundred.

      [2]
    3

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    0 / 8

    The resting body temperature, in degrees °C, of 6 adults is measured and recorded alongside their age, in years, in the table below.

    Age (Y)

    41

    46

    49

    51

    55

    61

    Temperature (C)

    37.7

    37.2

    37.1

    39.2

    36.8

    36.6

    1. State the age of the outlier in this data set.

      [1]
    2. Suggest one reason the outlier identified in (a) should not be included in any further analysis.

      [1]

    The relationship between Y and C can be modelled by the equation C =aY+b.

    1. Find the value of a and the value of b.

      [2]
    2. Find and interpret the value of Pearson's product-moment correlation coefficient, r, for these data.

      [2]
    3. Use the model C =aY+b to estimate the body temperature of a newborn, and explain why this is unlikely to be reliable.

      [2]
    4

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    A teacher surveys his class to find out how long each student spent studying for a recent test. The time, in hours, each student spent studying is shown alongside their score in the following table.

    Study time (h)

    0

    1

    2

    4

    5

    8

    Score (s)

    45

    52

    62

    65

    74

    88

    1. Find and interpret Pearson's product-moment correlation coefficient, r, for this data.

      [2]
    2. Find the equation of the regression line of s on t.

      [2]
    3. Use the regression line found in (b) to predict the score of a student who spent 7 hours studying.

      [2]
    4. Explain why the regression equation should not be used to predict the score of a student who studied 25 hours for the test.

      [1]
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    Lessons

    Feeling shaky on the material? Check out a lesson:

    Thumbnail for Population & Data

    Understand the basics of population, data collection, and sampling.

    Population & Data
    Thumbnail for Measuring Center

    Learn different ways to measure the "center," or typical values, of a set of data: mean, median, and mode.

    Measuring Center
    Thumbnail for Quartiles and Box & Whisker Plots

    Learn the concept of dispersion, range, IQR, outliers, and box and whisker plots.

    Quartiles and Box & Whisker Plots (Plus Only)
    Thumbnail for Standard Deviation and Variance

    Learn about standard deviation and variance, which we use to measure how tightly or loosely clustered the data is around the mean.

    Standard Deviation and Variance (Plus Only)
    Thumbnail for Frequency Tables, Histograms and cumulative frequency diagrams

    In this lesson, we learn about different ways to visualize frequency data, including tables, histograms, and cumulative frequency diagrams.

    Frequency Tables, Histograms and cumulative frequency diagrams (Plus Only)
    Thumbnail for Linear Regression

    Regressions of y on x, regressions of x on y, the correlation coefficient r, the rank correlation coefficient rs​, extrapolation and interpolation of data.

    Linear Regression (Plus Only)