The video discusses the balance between methodological and conceptual rigor, emphasizing the importance of understanding the object of study. It highlights the need for philosophical inquiry to determine appropriate methods and explanations. The speaker explores how different methods in social sciences, such as formal models, case studies, and statistical analyses, offer varied explanations and the challenge of making these compatible.

What is the main difference between methodological and conceptual rigor?

• Conceptual rigor is about statistical analysis, while methodological rigor is about philosophical thinking.

• Methodological rigor focuses on the appropriateness of methods, while conceptual rigor involves understanding the object of study.

• Methodological rigor is about the significance of numbers, while conceptual rigor is about the correlation of data.

• Conceptual rigor is about the appropriateness of methods, while methodological rigor involves understanding the object of study.

Why is philosophical thinking important in research methodology?

• It provides statistical significance to research findings.

• It ensures that all research methods are compatible.

• It helps in deciding the appropriate level of methodological rigor.

• It eliminates the need for conceptual rigor.

What was a common trend in social sciences research 10 years ago?

• Ignoring philosophical questions.

• Adopting multiple types of different methods.

• Using a single method for all research.

• Focusing solely on statistical analysis.

How do different research methods affect the explanation of phenomena?

• They generate explanations that are universally compatible.

• They suggest different modes of explanation.

• They always lead to the same explanation.

• They eliminate the need for philosophical work.

What is the role of philosophical work in research with multiple methods?

• To make different explanations compatible.

• To eliminate the need for methodological rigor.

• To focus solely on conceptual rigor.

• To ensure all methods are statistically significant.