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In statistics, the frequency or absolute frequency of an event is the number of times the observation has occurred/been recorded in an experiment or study. [ 1 ] : 12–19 These frequencies are often depicted graphically or tabular form.
If the mean =, the first factor is 1, and the Fourier transform is, apart from a constant factor, a normal density on the frequency domain, with mean 0 and variance /. In particular, the standard normal distribution φ {\textstyle \varphi } is an eigenfunction of the Fourier transform.
The number of claims N is a random variable, which is said to have a "claim number distribution", and which can take values 0, 1, 2, .... etc..For the "Panjer recursion", the probability distribution of N has to be a member of the Panjer class, otherwise known as the (a,b,0) class of distributions.
In statistics, an empirical distribution function (commonly also called an empirical cumulative distribution function, eCDF) is the distribution function associated with the empirical measure of a sample. [1]
This corresponds to the following non-logarithmic gain model: =, where = / is the average multiplicative gain at the reference distance from the transmitter. This gain depends on factors such as carrier frequency, antenna heights and antenna gain, for example due to directional antennas; and = / is a stochastic process that reflects flat fading.
The conversions between a frequency f and an angular frequency ω are ω = 2 π f , f = ω 2 π . {\displaystyle \omega =2\pi f,\quad f={\frac {\omega }{2\pi }}.} Thus a disc rotating at 60 rpm is said to have an angular speed of 2 π rad/s and a rotation frequency of 1 Hz.
In telecommunications and computing, bit rate (bitrate or as a variable R) is the number of bits that are conveyed or processed per unit of time. [1]The bit rate is expressed in the unit bit per second (symbol: bit/s), often in conjunction with an SI prefix such as kilo (1 kbit/s = 1,000 bit/s), mega (1 Mbit/s = 1,000 kbit/s), giga (1 Gbit/s = 1,000 Mbit/s) or tera (1 Tbit/s = 1,000 Gbit/s). [2]
The arithmetic mean (or simply mean or average) of a list of numbers, is the sum of all of the numbers divided by their count.Similarly, the mean of a sample ,, …,, usually denoted by ¯, is the sum of the sampled values divided by the number of items in the sample.