Abductive reasoning involves forming the most likely explanation from new, incomplete data and is widely used in medicine and complex problem-solving for generating insightful theories.

¶ abductive reasoning

Deductive research tests theories by gathering data to confirm or reject hypotheses, focusing on concrete conclusions rather than generating new knowledge or predicting future events.

¶ deductive reasoning

Falsifiability is the ability to prove a statement false and helps turn observations into scientific laws by seeking disconfirming evidence rather than just confirming data.

¶ falsifiability

Inductive research develops new theories by observing limited data, linking ideas creatively to form hypotheses that help predict future events or explain phenomena.

¶ inductive reasoning

Explore the key differences between qualitative and quantitative research methods, highlighting their unique strengths, weaknesses, and underlying philosophies for better data analysis and understanding.

≈ mixed methods

Discover the key differences between qualitative and quantitative research methods, their strengths in explanation and measurement, and how each offers unique insights for better understanding data.

Qualitative and quantitative research methods each have trade offs

Learn the key differences between qualitative and quantitative research, including their goals, methods, and how mixed-methods combine objective data with human context and meaning.

Qualitative and quantitative research represent different philosophies of knowledge

Qualitative research builds deep understanding of people’s motivations and contexts, helping create better products by revealing what truly matters through open-ended, narrative-driven insights.

Qualitative research creates mental models about the problem space

Qualitative research explains causation using metaphors and narratives to create concepts for quantitative testing, offering deep insights beyond event frequency and complementing quantitative methods.

Qualitative research excels at explanation

Learn how qualitative UX research focuses on data saturation over sample size to uncover key user insights and improve products through ongoing Agile feedback and diverse user interviews.

Qualitative researchers care more about data saturation than sample size

Quantitative analysis can be biased and limited, as data selection and interpretation depend on human judgment and may overlook context and deeper understanding of human behavior.

UX > Mixed methods

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January (11 posts)