  Microvariations probe the physics and internal structure of quasars.
Unpredictability and small flux variations make this phenomenon elusive and
difficult to detect. Variance based probes such as the C and F tests, or a
combination of both, are popular methods to compare the light-curves of the
quasar and a comparison star. Recently, detection claims in some studies depend
on the agreement of the results of the C and F tests, or of two instances of
the F-test, in rejecting the non-variation null hypothesis. However, the C-test
is a non-reliable statistical procedure, the F-test is not robust, and the
combination of tests with concurrent results is anything but a straightforward
methodology. A priori Power Analysis calculations and post hoc analysis of
Monte-Carlo simulations show excellent agreement for the Analysis of Variance
test to detect microvariations, as well as the limitations of the F-test.
Additionally, combined tests yield correlated probabilities that make the
assessment of statistical significance unworkable. However, it is possible to
include data from several field stars to enhance the power in a single F-test,
increasing the reliability of the statistical analysis. This would be the
preferred methodology when several comparison stars are available. An example
using two stars and the enhanced F-test is presented. These results show the
importance of using adequate methodologies, and avoid inappropriate procedures
that can jeopardize microvariability detections. Power analysis and Monte-Carlo
simulations are useful tools for research planning, as they can reveal the
robustness and reliability of different research approaches.
