Sampling is a means of obtaining a discrete data set from an analog or continuous signal of interest. This is usually done digitally by computers and multimeters. Some important considerations are sample rate, resolution, range, and the family of variables related to it. 1) The sample rate corresponds to a frequency, the sample rate which is a measure of the frequency at which a signal of interest is measured. In the most common case the signal of interest is time dependent, the sampling frequency must meet certain requirements in order to provide accurate information. The sampling frequency or sample rate has a direct relationship with the amount of information per unit of time that can be known about the signal of interest: the higher this frequency, the more accurately the measured signal can be represented . At the other extreme, the sampling rate may be too slow to be used to reconstruct the continuous signal. 2) The sampling theorem predicts that the sampling rate must be at least twice as large as the lowest frequency. higher of the measured signal of interest. Since the sampling frequency is that of one period of the signal, the Nyquist frequency, also called aliasing frequency, is less than or equal to half the sampling frequency of a discrete signal processing system. If the Nyquist frequency is too high, the system exhibits imperfect signaling called aliasing. Additionally, the Nyquist frequency establishes the number of harmonics that can be measured, i.e. harmonics can be measured up to fnyq. Equations 7.2, 7.3?3) Aliasing is a phenomenon that leads to misinterpretation of data. When the sampling rate on a continuous signal is less than twice the highest measured frequency, the resulting discrete series appears to have a frequency...... middle of paper ......nshape, which allows for a softer average throughout the length. frequency outputs.12) The most important factors when discussing data acquisition are range, sample rate, and resolution. First, range and resolution collaborate due to quantization error. Since it is defined as input values ​​coded to match adjacent coded outputs, the resolution is imperative because it determines the smallest step size at which outputs are collected; the smaller the step size, the better the accuracy because the sensitivity will increase. If the range of selected values ​​also increases, the sensitivity will not change but the accuracy will be much better. The sampling frequency is crucial because it decides what the Nyquist or aliasing frequency will be, which allows the user to know what frequencies the signals are aliasing and how many such harmonics there would be..