
TL;DR
This paper evaluates various statistical tests for detecting microvariability in AGN lightcurves, emphasizing the importance of using well-tested, unbiased methods to improve research reliability.
Contribution
It provides a comprehensive comparison of statistical methodologies for AGN microvariability detection, highlighting the robustness of ANOVA and chi-square tests.
Findings
ANOVA and chi-square tests are effective for microvariability detection.
C-statistics is unreliable and should be avoided.
Properly tested methods reduce biased results in AGN studies.
Abstract
Literature on optical and infrared microvariability in Active Galactic Nuclei (AGNs) reflects a diversity of statistical tests and strategies to detect tiny variations in the lightcurves of these sources. Comparison between the results obtained using different methodologies is difficult, and the pros and cons of each statistical method are often badly understood or even ignored. Even worse, not properly tested methodologies are becoming more and more common, and biased results may be misleading to realize the origin of the AGN microvariability. This paper intends to point future research on AGN microvariability to the use of powerful and well tested statistical methodologies, providing a reference for choosing the best strategy to obtain unbiased results. Lightcurves monitoring have been simulated for quasars, reference and comparison stars. Changes for the quasar lightcurves include…
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