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  2. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    [2] [3] Probability density is the probability per unit length, in other words, while the absolute likelihood for a continuous random variable to take on any particular value is 0 (since there is an infinite set of possible values to begin with), the value of the PDF at two different samples can be used to infer, in any particular draw of the ...

  3. Notation in probability and statistics - Wikipedia

    en.wikipedia.org/wiki/Notation_in_probability...

    Random variables are usually written in upper case Roman letters, such as or and so on. Random variables, in this context, usually refer to something in words, such as "the height of a subject" for a continuous variable, or "the number of cars in the school car park" for a discrete variable, or "the colour of the next bicycle" for a categorical variable.

  4. Template:List of statistics symbols - Wikipedia

    en.wikipedia.org/wiki/Template:List_of...

    In general, the subscript 0 indicates a value taken from the null hypothesis, H 0, which should be used as much as possible in constructing its test statistic. ... Definitions of other symbols: Definitions of other symbols:

  5. Correlogram - Wikipedia

    en.wikipedia.org/wiki/Correlogram

    In the analysis of data, a correlogram is a chart of correlation statistics. For example, in time series analysis, a plot of the sample autocorrelations versus (the time lags) is an autocorrelogram. If cross-correlation is plotted, the result is called a cross-correlogram.

  6. Sample mean and covariance - Wikipedia

    en.wikipedia.org/wiki/Sample_mean_and_covariance

    The arithmetic mean of a population, or population mean, is often denoted μ. [2] The sample mean ¯ (the arithmetic mean of a sample of values drawn from the population) makes a good estimator of the population mean, as its expected value is equal to the population mean (that is, it is an unbiased estimator).

  7. Prediction interval - Wikipedia

    en.wikipedia.org/wiki/Prediction_interval

    Given a sample from a normal distribution, whose parameters are unknown, it is possible to give prediction intervals in the frequentist sense, i.e., an interval [a, b] based on statistics of the sample such that on repeated experiments, X n+1 falls in the interval the desired percentage of the time; one may call these "predictive confidence intervals".

  8. Completely randomized design - Wikipedia

    en.wikipedia.org/wiki/Completely_randomized_design

    In practice, the randomization is typically performed by a computer program. However, the randomization can also be generated from random number tables or by some physical mechanism (e.g., drawing the slips of paper).

  9. Rutherford scattering experiments - Wikipedia

    en.wikipedia.org/wiki/Rutherford_scattering...

    Rutherford scattering cross-section is strongly peaked around zero degrees, and yet has nonzero values out to 180 degrees. This formula predicted the results that Geiger measured in the coming year. The scattering probability into small angles greatly exceeds the probability in to larger angles, reflecting the tiny nucleus surrounded by empty ...