sampling theorem is used to know about sample signal.
The Central Limit THeorem say that the sampling distribution of .. is ... It would help if you read your question before posting it.
the central limit theorem
Thanks to the Central Limit Theorem, the sampling distribution of the mean is Gaussian (normal) whose mean is the population mean and whose standard deviation is the sample standard error.
Answer is Quota sampling. Its one of the method of non-probability sampling.
sampling theorem is used to know about sample signal.
sampling theorem is defined as , the sampling frequency should be greater than or equal to 2*maximum frequency, and the frequency should be bounded.. i,e fs=2*fmax where fs= sampling frequency
The Central Limit THeorem say that the sampling distribution of .. is ... It would help if you read your question before posting it.
applied in making of aeroplane wings
I cannot see where the Nyquist theorem relates to cables, fiber or not.The theorem I know, the Nyquist-Shannon sampling theorem, talks about the limitations in sampling a continuous (analog) signal at discrete intervals to turn it into digital form.An optical fiber or other cable merely transport bits, there is no analog/digital conversion and no sampling taking place.
sampling is a one type of process use for converting into analog signal to digital signal.
Sampling Theorum is related to signal processing and telecommunications. Sampling is the process of converting a signal into a numeric sequence. The sampling theorum gives you a rule using DT signals to transmit or receive information accurately.
This is the Central Limit Theorem.
the central limit theorem
The Nyquist Theorem says that the sampling frequency should be twice the bandwidth to avoid aliasing. Thus if the bandwidth of the system is bw then the sampling frequency f=2*bw.
the process of deducing a new formula, theorem, etc., from previously accepted statements. • a sequence of statements showing that a formula, theorem, etc., is a consequence of previously accepted statements.
The Nyquist-Shannon sampling theorem states that in order to accurately capture a waveform, the sampling frequency must be at least twice the frequency of the waveform. If the sampling frequency is too low compared to the waveform frequency, aliasing can occur, resulting in distorted representations of the waveform.