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  2. Standard normal table - Wikipedia

    en.wikipedia.org/wiki/Standard_normal_table

    To find a negative value such as -0.83, one could use a cumulative table for negative z-values [3] which yield a probability of 0.20327. But since the normal distribution curve is symmetrical, probabilities for only positive values of Z are typically given.

  3. Z-test - Wikipedia

    en.wikipedia.org/wiki/Z-test

    Looking up the z-score in a table of the standard normal distribution cumulative probability, we find that the probability of observing a standard normal value below −2.47 is approximately 0.5 − 0.4932 = 0.0068.

  4. 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.

  5. Beverton–Holt model - Wikipedia

    en.wikipedia.org/wiki/Beverton–Holt_model

    The Beverton–Holt model is a classic discrete-time population model which gives the expected number n t+1 (or density) of individuals in generation t + 1 as a function of the number of individuals in the previous generation,

  6. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    This is a special case when = and =, and it is described by this probability density function (or density): =. The variable z {\textstyle z} has a mean of 0 and a variance and standard deviation of 1.

  7. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    The following table lists values for t distributions with ν degrees of freedom for a range of one-sided or two-sided critical regions. The first column is ν , the percentages along the top are confidence levels α , {\displaystyle \ \alpha \ ,} and the numbers in the body of the table are the t α , n − 1 {\displaystyle t_{\alpha ,n-1 ...

  8. Density estimation - Wikipedia

    en.wikipedia.org/wiki/Density_Estimation

    The unobservable density function is thought of as the density according to which a large population is distributed; the data are usually thought of as a random sample from that population. [1] A variety of approaches to density estimation are used, including Parzen windows and a range of data clustering techniques, including vector quantization.

  9. 97.5th percentile point - Wikipedia

    en.wikipedia.org/wiki/97.5th_percentile_point

    In Table 1 of the same work, he gave the more precise value 1.959964. [12] In 1970, the value truncated to 20 decimal places was calculated to be 1.95996 39845 40054 23552... [13] [14] The commonly used approximate value of 1.96 is therefore accurate to better than one part in 50,000, which is more than adequate for applied work.