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  2. Standard normal table - Wikipedia

    en.wikipedia.org/wiki/Standard_normal_table

    Since probability tables cannot be printed for every normal distribution, as there are an infinite variety of normal distributions, it is common practice to convert a normal to a standard normal (known as a z-score) and then use the standard normal table to find probabilities.

  3. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The simplest case of a normal distribution is known as the standard normal distribution or unit normal distribution. This is a special case when μ = 0 {\textstyle \mu =0} and σ 2 = 1 {\textstyle \sigma ^{2}=1} , and it is described by this probability density function (or density): φ ( z ) = e − z 2 2 2 π . {\displaystyle \varphi (z ...

  4. x̅ and s chart - Wikipedia

    en.wikipedia.org/wiki/X̅_and_s_chart

    The normal distribution is the basis for the charts and requires the following assumptions: The quality characteristic to be monitored is adequately modeled by a normally-distributed random variable; The parameters μ and σ for the random variable are the same for each unit and each unit is independent of its predecessors or successors

  5. 97.5th percentile point - Wikipedia

    en.wikipedia.org/wiki/97.5th_percentile_point

    In probability and statistics, the 97.5th percentile point of the standard normal distribution is a number commonly used for statistical calculations. The approximate value of this number is 1.96 , meaning that 95% of the area under a normal curve lies within approximately 1.96 standard deviations of the mean .

  6. Probit - Wikipedia

    en.wikipedia.org/wiki/Probit

    Plot of probit function. In probability theory and statistics, the probit function is the quantile function associated with the standard normal distribution.It has applications in data analysis and machine learning, in particular exploratory statistical graphics and specialized regression modeling of binary response variables.

  7. Q-function - Wikipedia

    en.wikipedia.org/wiki/Q-function

    In statistics, the Q-function is the tail distribution function of the standard normal distribution. [ 1 ] [ 2 ] In other words, Q ( x ) {\displaystyle Q(x)} is the probability that a normal (Gaussian) random variable will obtain a value larger than x {\displaystyle x} standard deviations.

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  9. Sten scores - Wikipedia

    en.wikipedia.org/wiki/Sten_scores

    The individual sten scores are defined by reference to a standard normal distribution. Unlike stanine scores, which have a midpoint of five, sten scores have no midpoint (the midpoint is the value 5.5). Like stanines, individual sten scores are demarcated by half standard deviations.