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This thesis describes signal analysis methods for single-molecule fluorescence data. The primary factor motivating method development is the need to distinguish single-molecule FRET fluctuations due to conformational dynamics from fluctuations due to distance-independent FRET changes. Single-molecule Förster resonance energy transfer (FRET) promises a distinct advantage compared to alternative biochemical methods in its potential to relate biomolecular structure to function. Standard measurements assume that the mean transfer efficiency between two fluorescent probes, a donor and an acceptor, corresponds to the mean donor-acceptor distance, thus providing structural information. Accordingly, measurement analysis assumes that mean transfer efficiency fluctuations entail mean donor-acceptor distance fluctuations. Detecting such fluctuations is important in resolving molecular dynamics, as molecular function often necessitates structural changes. A problem arises, however, in that factors other than donor-acceptor distance changes may induce mean transfer efficiency fluctuations. We refer to these factors as distance-independent FRET changes. We present analysis methods to detect distance-independent photophysical dynamics and to determine their correlation with distance-dependent FRET dynamics. First, we review a theory of photon statistics and show how we can use the theory to detect FRET fluctuations. Second, we extend the theory to alternating laser excitation (ALEx) measurements and demonstrate how fluorophore stoichiometry, a measure of fluorophore brightness, reports on distance-independent photophysical dynamics. Next, we provide a measure to determine the extent to which stoichiometry fluctuations account for FRET dynamics. Finally, we use a framework similar to the preceding along with recent advances in the theory of total internal reflection fluorescence (TIRF) microscopy FRET measurements to detect TIRF FRET fluctuations which occur on a timescale faster than the measurement temporal resolution. We validate our methods with simulations and demonstrate their utility in delineating RNA polymerase open complex conformational dynamics.