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  2. Standard score - Wikipedia

    en.wikipedia.org/wiki/Standard_score

    Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.

  3. Normal curve equivalent - Wikipedia

    en.wikipedia.org/wiki/Normal_curve_equivalent

    where z is the standard score or "z-score", i.e. z is how many standard deviations above the mean the raw score is (z is negative if the raw score is below the mean). The reason for the choice of the number 21.06 is to bring about the following result: If the scores are normally distributed (i.e. they follow the "bell-shaped curve") then

  4. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    If instead of a classroom, we considered a subregion containing 900 students whose mean score was 99, nearly the same z-score and p-value would be observed. This shows that if the sample size is large enough, very small differences from the null value can be highly statistically significant.

  5. Standard normal table - Wikipedia

    en.wikipedia.org/wiki/Standard_normal_table

    Z tables use at least three different conventions: Cumulative from mean gives a probability that a statistic is between 0 (mean) and Z. Example: Prob(0 ≤ Z ≤ 0.69) = 0.2549. Cumulative gives a probability that a statistic is less than Z. This equates to the area of the distribution below Z. Example: Prob(Z ≤ 0.69) = 0.7549.

  6. Normal score - Wikipedia

    en.wikipedia.org/wiki/Normal_score

    The term normal score is used with two different meanings in statistics. One of them relates to creating a single value which can be treated as if it had arisen from a standard normal distribution (zero mean, unit variance). The second one relates to assigning alternative values to data points within a dataset, with the broad intention of ...

  7. Fisher transformation - Wikipedia

    en.wikipedia.org/wiki/Fisher_transformation

    The application of Fisher's transformation can be enhanced using a software calculator as shown in the figure. Assuming that the r-squared value found is 0.80, that there are 30 data [clarification needed], and accepting a 90% confidence interval, the r-squared value in another random sample from the same population may range from 0.656 to 0.888.

  8. 97.5th percentile point - Wikipedia

    en.wikipedia.org/wiki/97.5th_percentile_point

    There is no single accepted name for this number; it is also commonly referred to as the "standard normal deviate", "normal score" or "Z score" for the 97.5 percentile point, the .975 point, or just its approximate value, 1.96. If X has a standard normal distribution, i.e. X ~ N(0,1),

  9. Percentile rank - Wikipedia

    en.wikipedia.org/wiki/Percentile_rank

    Occasionally the percentile rank of a score is mistakenly defined as the percentage of scores lower than or equal to it [citation needed], but that would require a different computation, one with the 0.5 × F term deleted. Typically percentile ranks are only computed for scores in the distribution but, as the figure illustrates, percentile ...