## 9 Conclusions  
In this study, a straightforward analytical expression was developed to determine the standard deviation of the estimated amplitude of a sinewave using the least squares method in the presence of jitter or phase noise. The derivation employed a first-order Taylor series approximation, which was validated through both numerical simulations and experimental data using a Monte Carlo approach. The resulting expression not only facilitates the calculation of confidence intervals for sinusoidal amplitude estimation but also aids in determining the number of signal samples required to achieve the desired level of estimation precision. The experimental setup was described in detail, comprising two function generators and a data acquisition module. The software, developed using National Instruments LabVIEW, was briefly outlined, though its complexity limited a thorough explanation. The level of jitter/phase noise was controlled by phase-modulating the clock signal that times the sample acquisition in the data acquisition module. The injected jitter/phase noise followed a zero-mean normal distribution with an adjustable standard deviation. The Monte Carlo method was utilized to estimate the standard deviation of the amplitude, repeated across various levels of injected jitter/phase noise. The results revealed a nearly linear relationship between the estimated sinusoidal amplitude and the standard deviation of jitter. However, a 16% discrepancy in the slope of this relationship was observed, the cause of which remains unexplained. It is important to note that several non-ideal factors were present in the experimental setup, including additive voltage noise, quantization error, intrinsic jitter in the sampling module, phase noise in the stimulus signal and clock generators, and limited noise bandwidth in both the function generator and data acquisition module. These factors are believed to be independent of the injected jitter/phase noise, contributing a constant offset to the experimental results rather than an error proportional to the jitter/phase noise standard deviation. Additionally, these factors affect both the sinewave amplitude estimation and the jitter/phase noise estimation processes. The unaccounted-for non-ideal phenomena must be proportional to the amount of jitter/phase noise introduced. Notably, no discrepancies were observed in the numerical simulations, reinforcing the validity of the analytical derivations and the developed software. This suggests that the discrepancy is likely due to an unaccounted hardware-related phenomenon not addressed in this work. The main result of this work is the derivation of the analytical relationship between phase noise/jitter standard deviation and sinusoidal amplitude estimation precision. A more complex but more accurate analytical expression was obtained, namely Equation (26). A simpler but approximate expression was obtained for the case of low phase noise/jitter standard deviation. This expression, namely Equation (27), shows a linear relationship between phase noise and jitter standard deviation and sinusoid amplitude estimation standard deviation. Furthermore, the current document explained in detail the experimental setup used and the steps taken to calibrate the amount of phase noise present. This can certainly be used by other researchers performing similar experiments involving the use of phase noise or jitter in the test setups. In the future, one might continue the work presented here by considering, for example, the uncertainty in both amplitude and initial phase in the presence of jitter or phase noise when using the four-parameter sine fitting algorithm where the signal frequency is not known and must be estimated using an iterative procedure. The same goes for the other estimators mentioned in Section 5.