James Mahoney and Gary Goertz contrast quantitative and qualitative research traditions as distinct cultures with different practices, beliefs, and norms. They argue that understanding these differences can help scholars avoid misunderstandings and improve communication in political science. The two traditions differ in their approaches to explanation, causation, multivariate analysis, equifinality, scope of generalization, case selection, weighting observations, substantively important cases, lack of fit, and concepts and measurement. Quantitative researchers focus on average causal effects across populations, while qualitative researchers aim to explain outcomes in specific cases. Quantitative methods often use controlled experiments and statistical models to estimate average effects, whereas qualitative methods rely on causal-process observations and logical analysis. The authors emphasize that both approaches have value and should be used appropriately depending on research goals. They argue that qualitative researchers often focus on identifying causal paths to outcomes, while quantitative researchers aim to generalize about average effects. The two traditions also differ in case selection, with qualitative researchers often selecting cases where the outcome of interest occurred, while quantitative researchers typically use random selection. Weighting observations also differs, with qualitative researchers placing more emphasis on critical observations, while quantitative researchers treat all observations equally. The authors conclude that both traditions have valid methods and should be used in ways that align with their respective goals.James Mahoney and Gary Goertz contrast quantitative and qualitative research traditions as distinct cultures with different practices, beliefs, and norms. They argue that understanding these differences can help scholars avoid misunderstandings and improve communication in political science. The two traditions differ in their approaches to explanation, causation, multivariate analysis, equifinality, scope of generalization, case selection, weighting observations, substantively important cases, lack of fit, and concepts and measurement. Quantitative researchers focus on average causal effects across populations, while qualitative researchers aim to explain outcomes in specific cases. Quantitative methods often use controlled experiments and statistical models to estimate average effects, whereas qualitative methods rely on causal-process observations and logical analysis. The authors emphasize that both approaches have value and should be used appropriately depending on research goals. They argue that qualitative researchers often focus on identifying causal paths to outcomes, while quantitative researchers aim to generalize about average effects. The two traditions also differ in case selection, with qualitative researchers often selecting cases where the outcome of interest occurred, while quantitative researchers typically use random selection. Weighting observations also differs, with qualitative researchers placing more emphasis on critical observations, while quantitative researchers treat all observations equally. The authors conclude that both traditions have valid methods and should be used in ways that align with their respective goals.