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  2. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    Z-test tests the mean of a distribution. For each significance level in the confidence interval, the Z-test has a single critical value (for example, 1.96 for 5% two tailed) which makes it more convenient than the Student's t-test whose critical values are defined by the sample size (through the corresponding degrees of freedom). Both the Z ...

  3. Test statistic - Wikipedia

    en.wikipedia.org/wiki/Test_statistic

    (Normal populations or n 1 + n 2 > 40) and independent observations and σ 1 ≠ σ 2 both unknown One-proportion z-test = ^ n. p 0 > 10 and n (1 − p 0) > 10 and it is a SRS (Simple Random Sample), see notes.

  4. Population proportion - Wikipedia

    en.wikipedia.org/wiki/Population_Proportion

    To derive the formula for the one-sample proportion in the Z-interval, a sampling distribution of sample proportions needs to be taken into consideration. The mean of the sampling distribution of sample proportions is usually denoted as μ p ^ = P {\displaystyle \mu _{\hat {p}}=P} and its standard deviation is denoted as: [ 2 ]

  5. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    The interesting result is that consideration of a real population and a real sample produced an imaginary bag. The philosopher was considering logic rather than probability. To be a real statistical hypothesis test, this example requires the formalities of a probability calculation and a comparison of that probability to a standard.

  6. Paired difference test - Wikipedia

    en.wikipedia.org/wiki/Paired_difference_test

    Suppose we are using a Z-test to analyze the data, where the variances of the pre-treatment and post-treatment data σ 1 2 and σ 2 2 are known (the situation with a t-test is similar). The unpaired Z-test statistic is ¯ ¯ / + /, The power of the unpaired, one-sided test carried out at level α = 0.05 can be calculated as follows:

  7. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]

  8. Standard normal table - Wikipedia

    en.wikipedia.org/wiki/Standard_normal_table

    Example: Prob(Z ≤ 0.69) = 0.7549. Complementary cumulative gives a probability that a statistic is greater than Z. This equates to the area of the distribution above Z. Example: Find Prob(Z ≥ 0.69). Since this is the portion of the area above Z, the proportion that is greater than Z is found by subtracting Z from 1.

  9. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    1 in 390 682 215 445: Every 1.07 billion years (four occurrences in history of Earth) μ ± 7.5σ: 0.999 999 999 999 936: 6.382 × 10 −14 = 63.82 ppq: 1 in 15 669 601 204 101: Once every 43 billion years (never in the history of the Universe, twice in the future of the Local Group before its merger) μ ± 8σ: 0.999 999 999 999 999: 1.244 × ...