Analysis and results (Chapters 2-5) of the full 7 year Macho Project dataset toward the Galactic bulge are presented. A total of 450 high quality, relatively large signal-to-noise ratio, events are found, including several events exhibiting exotic effects, and lensing events on possible Sagittarius dwarf galaxy stars. We examine the problem of blending in our sample and conclude that the subset of red clump giants are minimally blended. Using 42 red clump giant events near the Galactic center we calculate the optical depth toward the Galactic bulge to be [pi] = 2.17calculate the optical depth toward the Galactic bulge to be [pi] =± +0.47-0.38 x 10⁻⁶ at (l,b) = (1.50⁰, -2.68⁰) with a gradient of (1.06 ± 0.71) x 10⁻⁶ deg⁻¹ in latitude, and (0.29 ± 0.43 x 10⁻⁶ deg⁻¹ in longitude, bringing measurements into consistency with the models for the first time. In Chapter 6 we reexamine the usefulness of fitting blended light- curve models to microlensing photometric data. We find agreement with previous workers (e.g. Woźniak ; Paczyński) that this is a difficult proposition because of the degeneracy of blend fraction with other fit parameters. We show that follow-up observations at specific points along the light curve (peak region and wings) of high magnification events are the most helpful in removing degeneracies. We also show that very small errors in the baseline magnitude can result in problems in measuring the blend fraction, and study the importance of non-Gaussian errors in the fit results. The biases and skewness in the distribution of the recovered blend fraction is discussed. We also find a new approximation formula relating the blend fraction and the unblended fit parameters to the underlying event duration needed to estimate microlensing optical depth. In Chapter 7 we present work-in-progress on the possibility of correcting standard candle luminosities for the magnification due to weak lensing. We consider the importance of lenses in different mass ranges and look at the contribution from lenses that could not be observed. We conclude that it may be possible to perform this correction with relatively high precision (1-2%) and discuss possible sources of error and methods of improving our model