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  • Perplex
    IB Math AIHL
    /
    Inference & Hypotheses
    /

    Z-test and Confidence Intervals

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    Exercises

    Key Skills

    Z-test and Confidence Intervals

    Z-test and Confidence Intervals

    Z-tests when the standard deviation is known, confidence intervals using Z and T distributions, critical values & regions, type Ⅰ vs ⅠⅠ errors.

    Want a deeper conceptual understanding? Try our interactive lesson!

    Exercises

    No exercises available for this concept.

    Practice exam-style z-test and confidence intervals problems

    Key Skills

    Normal confidence interval using technology
    AHL AI 4.16

    Your calculator should include a statistical test called Zinterval or similar. To use it:

    1. Enter the value of ​σ, which must be known for a Z-test of any kind.

    2. Enter either

      • Data: a list of values you've typed into the calculator

      • Stats: the sample mean ​xˉ​ and ​n, the number of samples.

    3. Enter the confidence level and hit calculate

    The calculator returns the desired interval, which is symmetrical around ​xˉ.

    T-interval confidence interval using technology
    AHL AI 4.16

    Your calculator should include a statistical test called Tinterval or similar. To use it:

    1. Enter either

      • Data: a list of values you've typed into the calculator

      • Stats: the sample mean ​xˉ, the sample standard deviation ​Sx​ and ​n, the number of samples.

    2. Enter the confidence level and hit calculate

    The calculator returns the desired interval, which is symmetrical around ​xˉ.

    Z-Test for population mean
    AHL AI 4.18

    Z-tests allow us to test the mean of a sample against

    • a population with known mean: use Z-Test

    • another sample: use 2-SampZTest

    • a paired sample: calculate the difference, then use Z-Test with ​μ0​=0.

    Critical values & regions
    AHL AI 4.18

    When testing the mean of a sample against a population, the critical region is the set of values for the sample mean that would lead to rejecting the null hypothesis. The critical value(s) is (are) the boundary of the critical region. In other words, the critical value is the threshold for ​xˉ​ that leads to a ​p​ value exactly equal to the chosen significance level.

    ​μ<μ0​​

    ​μ=μ0​​

    ​μ0​<μ​

    ​c=invNorm(p,μ,σ,LEFT)​

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    ​c=invNorm(1−p,μ,σ,CENTER)​

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    ​c=invNorm(p,μ,σ,RIGHT)​

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