This thesis brings statistical analyses techniques to bear on data derived from an extensive database of satellite launches and on-orbit anomalies and failures. The data collected is analyzed from two different perspectives and addresses, in two separate studies, two research objectives. The first study proposes to identify trends and cyclical patterns in the space industry, and to forecast the volume of launches for the next few years. Satellites have been rightfully described as the lifeblood of the entire space industry and the number of satellites ordered or launched per year is an important defining metric of the industry's level of activity. The structure of the space industry, its financial health and its workforce retention and development is dependent on the volume of satellites contracted. As such, trends and variability in this volume have significant strategic impact on the space industry. Over the past 40+ years, hundreds of satellites have been launched every year. Thus, an important data set is available for time series analysis and identification of trends and cycles in the various markets of the space industry. For the purpose of this first study, we collected data for over 6,000 satellites launched since 1960 on a yearly basis. We separated the satellites into three broad segments: 1) defense and intelligence satellites, 2) science satellites, and 3) commercial satellites. Several techniques are available for the analysis of time series data, both in the time domain and in the frequency domain. In this first study, we conducted spectral analysis of the time series for each of the three satellite populations and identified cycles contained in the data. In addition, once harmonic models were derived and fitted to the data, we built forecasting models of satellite launch volumes in the different market segments for the next few years. The potential implications of the results are discussed as a number of strategic matters for the space industry are contingent on the predictions or forecast of the volume of satellites contracted (the example of the U.S. auto industry is a solemn reminder of such possible strategic issues). The second study uses the previously collected launch data, confined to Earth-orbiting satellites launched between 1990 and 2008, and expanded with the failure information and retirement of each satellite to conduct a comparative analysis of satellite reliability in GEO, LEO, and MEO orbits. Reliability has long been recognized as an essential consideration in the design of space systems. However, there is limited statistical analysis of satellite reliability based on actual flight data. The objective of this second study is to conduct nonparametric satellite reliability analysis, with orbit type as a covariate, and to explore appropriate parametric fits (Weibull, lognormal, and mixture distributions). The results indicate for example that differences exist between the failure behaviors of satellites in different orbits, or that satellite infant mortality exists or dominates more clearly in a particular orbit type. The findings can be useful to satellite manufacturers as they would provide an empirical basis for reviewing and adjusting satellite testing and burn-in procedures.