object T_Test1

The T_Test1 companion object provides a convenient method for performing t-test. If 'difference' is false (fail to reject), making a decision on this basis can be risky, so 'same' should be called. If neither 'different' or 'same' are true, need to collect more data.

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  1. final def !=(arg0: Any): Boolean
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  5. def c(df: Int, α: Double = 0.05): Double

    Return the critical value for the Student's t-distribution.

    Return the critical value for the Student's t-distribution. For a two-sided/two-tailed test, the critical values are '-c' and 'c' and the total probability mass in the tails being 'α'a.

    df

    the effective degrees of freedom

    α

    the desired sigificance level

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  7. def different(p: Double, α: Double = 0.05): Boolean

    Determine whether the difference in the two means is statistically significant.

    Determine whether the difference in the two means is statistically significant. If true, "reject" the null hypothesis that μ = μ0, else "fail to reject"

    p

    the probability of a Type I error

    α

    the desired sigificance level

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  16. def same(p2: Double, pw: Double = 0.9): Boolean

    Determine whether the difference in the two means is statistically insignificant.

    Determine whether the difference in the two means is statistically insignificant. Note, typically this is a weaker test than 'different'.

    p2

    the probability of a Type II error

    pw

    the desired power level (p2 = 1 - power)

  17. final def synchronized[T0](arg0: ⇒ T0): T0
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  18. def test(x: VectorD, μ0: Double, α: Double = 0.05, pw: Double = 0.9): Unit

    Perform a one-sample t-test based on comapring the sample mean with the "known" population mean.

    Perform a one-sample t-test based on comapring the sample mean with the "known" population mean.

    x

    the sample's vector of data

    μ0

    the "known" population mean

    α

    the desired sigificance level

    pw

    the desired power of the test

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