Rising tensions between police and minority communities in the late 1990s led to charges of racially biased policing in many cities throughout the United States. In response, law enforcement agencies around the country have implemented data collection and analysis efforts in which police officers collect data on drivers’ race when they make vehicle stops. The data allows agencies to analyze whether racially biased policing practices may be occurring. The two main goals of this guide are to inform stakeholders of the types of conclusions that can be reached with vehicle stop data and to describe how the data can be analyzed. Following the introduction in chapter 1, chapter 2 turns to a discussion of the benchmarking challenge which involves figuring out what percentage of vehicle stops involving minority groups would be indicative of racially biased policing. Chapter 3 describes the preliminary steps law enforcement agencies should take in the collection of police-citizen contact data, such as determining which law enforcement activities to collect data on and determining what type of information should be collected. Chapter 4 presents data analysis guidelines for all benchmarking methods while chapter 5 details several benchmarking methods and tools, including benchmarking with adjusted census data and benchmarking with DMV data. Chapter 6 presents guidelines for analyzing the post-stop activities of police officers because in many instances these post-stop activities are more likely to be influenced by racial bias than the initial vehicle stop. Chapter 7 describes the types of conclusions that can be drawn from vehicle stop data and chapter 8 discusses how to use the results for police reform. Tables, figures, footnotes, references, resources