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  2. Equivalent concentration - Wikipedia

    en.wikipedia.org/wiki/Equivalent_concentration

    Normality can be used for acid-base titrations. For example, sulfuric acid (H 2 SO 4) is a diprotic acid. Since only 0.5 mol of H 2 SO 4 are needed to neutralize 1 mol of OH −, the equivalence factor is: f eq (H 2 SO 4) = 0.5. If the concentration of a sulfuric acid solution is c(H 2 SO 4) = 1 mol/L, then its normality is 2 N. It can also be ...

  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. Mode (statistics) - Wikipedia

    en.wikipedia.org/wiki/Mode_(statistics)

    The mode of a sample is the element that occurs most often in the collection. For example, the mode of the sample [1, 3, 6, 6, 6, 6, 7, 7, 12, 12, 17] is 6. Given the list of data [1, 1, 2, 4, 4] its mode is not unique. A dataset, in such a case, is said to be bimodal, while a set with more than two modes may be described as multimodal.

  5. Normalizing constant - Wikipedia

    en.wikipedia.org/wiki/Normalizing_constant

    If we start from the simple Gaussian function = /, (,) we have the corresponding Gaussian integral = / =,. Now if we use the latter's reciprocal value as a normalizing constant for the former, defining a function () as = = / so that its integral is unit = / = then the function () is a probability density function. [3]

  6. Gaussian function - Wikipedia

    en.wikipedia.org/wiki/Gaussian_function

    Specifically, if the mass-density at time t=0 is given by a Dirac delta, which essentially means that the mass is initially concentrated in a single point, then the mass-distribution at time t will be given by a Gaussian function, with the parameter a being linearly related to 1/ √ t and c being linearly related to √ t; this time-varying ...

  7. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    Let and be respectively the cumulative probability distribution function and the probability density function of the ( , ) standard normal distribution, then we have that [2] [4] the probability density function of the log-normal distribution is given by:

  8. Gaussian integral - Wikipedia

    en.wikipedia.org/wiki/Gaussian_integral

    A different technique, which goes back to Laplace (1812), [3] is the following. Let = =. Since the limits on s as y → ±∞ depend on the sign of x, it simplifies the calculation to use the fact that e −x 2 is an even function, and, therefore, the integral over all real numbers is just twice the integral from zero to infinity.

  9. Colligative properties - Wikipedia

    en.wikipedia.org/wiki/Colligative_properties

    Here K f is the cryoscopic constant (equal to 1.86 °C kg/mol for the freezing point of water), i is the van 't Hoff factor, and m the molality (in mol/kg). This predicts the melting of ice by road salt. In the liquid solution, the solvent is diluted by the addition of a solute, so that fewer molecules are available to freeze.