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For a typical second-order reaction with rate equation = [] [], if the concentration of reactant B is constant then = [] [] = ′ [], where the pseudo–first-order rate constant ′ = []. The second-order rate equation has been reduced to a pseudo–first-order rate equation, which makes the treatment to obtain an integrated rate equation much ...
For the second-order approximations of the third central moment as well as for the derivation of all higher-order approximations see Appendix D of Ref. [3] Taking into account the quadratic terms of the Taylor series and the third moments of the input variables is referred to as second-order third-moment method. [4]
Stated in terms of odds, Bayes' rule states that the posterior odds of two alternatives, and , given an event , is the prior odds, times the likelihood ratio. As an equation: O ( A 1 : A 2 ∣ B ) = O ( A 1 : A 2 ) ⋅ Λ ( A 1 : A 2 ∣ B ) . {\displaystyle O(A_{1}:A_{2}\mid B)=O(A_{1}:A_{2})\cdot \Lambda (A_{1}:A_{2}\mid ...
Thus if expressed as a fraction with a numerator of 1, probability and odds differ by exactly 1 in the denominator: a probability of 1 in 100 (1/100 = 1%) is the same as odds of 1 to 99 (1/99 = 0.0101... = 0. 01), while odds of 1 to 100 (1/100 = 0.01) is the same as a probability of 1 in 101 (1/101 = 0.00990099... = 0. 0099). This is a minor ...
This has the same form as an equation for a straight line: = +, where x is the reciprocal of T. So, when a reaction has a rate constant obeying the Arrhenius equation, a plot of ln k versus T −1 gives a straight line, whose slope and intercept can be used to determine E a and A respectively. This procedure is common in experimental chemical ...
n th-order reaction (r = kC A n), where k is the reaction rate constant, C A is the concentration of species A, and n is the order of the reaction; isothermal conditions, or constant temperature (k is constant) single, irreversible reaction (ν A = −1) All reactant A is converted to products via chemical reaction; N A = C A V
A master equation is a phenomenological set of first-order differential equations describing the time evolution of (usually) the probability of a system to occupy each one of a discrete set of states with regard to a continuous time variable t.
In other words, the difference between the logarithm of the odds of having poor or fair health minus the logarithm of odds of having poor health is the same regardless of x; similarly, the logarithm of the odds of having poor, fair, or good health minus the logarithm of odds of having poor or fair health is the same regardless of x; etc. [2]