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    The weights of apples on a tree can be modelled by a normal distribution with a mean of85 grams and a standard deviation of 7.5 grams.A sample of apples are taken from 2 trees, A and B, in different parts of the orchard.The data is shown in the table below.The owner of the orchard wants to know whether the mean weight of the apples from treeA(μA) is greater than the mean weight of the apples from tree B(μB) so sets up thefollowing test:H0: μA=μBandH1: μA>μB

    Question
    SLPaper 1

    The weights of apples on a tree can be modelled by a normal distribution with a mean of85 grams and a standard deviation of 7.5 grams.

    A sample of apples are taken from 2 trees, A and B, in different parts of the orchard.

    The data is shown in the table below.

    The owner of the orchard wants to know whether the mean weight of the apples from treeA(μA) is greater than the mean weight of the apples from tree B(μB) so sets up thefollowing test:

    H0: μA=μBandH1: μA>μB

    1.

    Find the probability that an apple from the tree has a weight greater than 90 grams.

    [2]
    Verified
    Solution

    * This sample question was produced by experienced DP mathematics senior examiners to aid teachers in preparing for external assessment in the new MAA course. There may be minor differences in formatting compared to formal exam papers.

    Let the weight of an apple beX

    PX>90=0.2520.252492… (M1)A1

    [2 marks]

    2.

    Find the p-value for the owner’s test.

    [2]
    Verified
    Solution

    p-value =0.0189(0.018947…) (M1)A1

    [2 marks]

    3.

    The test is performed at the 5% significance level.

    State the conclusion of the test, giving a reason for your answer.

    [2]
    Verified
    Solution

    0.0189<0.05 R1

    Sufficient evidence to reject the null hypothesis (that the weights of apples from thetwo trees are equal) A1

    [2 marks]

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    Related topics

    SL 4.11—Expected, observed, hypotheses, chi squared, gof, t-testSL 4.9—Normal distribution
    Mathematics Applications & Interpretation (Math AI)
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