Abstract
The presentation is devoted to the study and evaluation of the statistical homogeneity of autocorrelated measurements, which is an important task in the analysis of time series and experimental data. The study will consider how autocorrelation affects statistical conclusions and the quality of parameter estimates. Particular attention is paid to methods of autocorrelation detection and data correction to ensure reliable analysis results. The report covers both theoretical aspects and practical examples of applying various methods for assessing statistical homogeneity in autocorrelated measurements. Autocorrelation can distort statistical conclusions, so the topic of researching such measurements and studying the correction methods that can be used to obtain more reliable results is relevant and not fully covered.
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