Signal & Noise

Exploratory research studies a problem nobody has defined yet. Definition, research design, 4 methods and 5 examples, and whether it is qualitative.

A focused interview is a one-to-one interview about one shared experience, from Merton and Kendall (1946). Definition, how it differs from a focus group, and 4 steps.

Purposive sampling means choosing participants deliberately. 7 types with examples (maximum variation, criterion, snowball and more) and how to justify them.

20 examples of qualitative data, from interview transcripts and field notes to survey comments and Reddit threads, grouped into 8 types with how each is used.

Qualitative data meaning: non-numerical information about experience and context. Definition, how it differs from quantitative data, and how to analyse it.

Types of variables in research explained with examples: independent, dependent, control, confounding, moderating, plus nominal, ordinal, interval and ratio.

Deductive coding applies a codebook from theory or research questions to qualitative data. A worked codebook example, 6 steps, and inductive vs deductive.

Descriptive coding examples from health, education, HR, customer and policy interviews: 25 excerpts with their codes, mistakes to avoid and how to do it.

Free datasets for qualitative research: interview archives, parliamentary speeches, open-ended surveys, reviews and literature, plus catalogues to find more.

A PhD student's guide to qualitative interview analysis: sample size, methods, transcription, coding by hand or with AI, and writing up, with links to go deeper.

Braun and Clarke's reflexive thematic analysis: what changed in 2019, 2021 and 2022, which paper to cite (with DOIs), the 6 phases and 5 common mistakes.

16 qualitative research examples from sociology, health, education, management and business, plus 5 student project ideas, each with its method and finding.

Reflecting on AI is a good practice, whether you use it or not. I argue to consider both the risks of losing ownership, but equally the opportunities of improving quality.

How AI fits across an ethnographic study: literature review, transcribing field notes and interviews, finding themes, and testing alternative framings.

A step-by-step walkthrough of Braun and Clarke's 6 phases of reflexive thematic analysis, with a real dataset example and guidance for PhD students.

Discourse analysis examines how language constructs meaning and power. This guide covers the main approaches, practical steps, and when to choose it over thematic analysis.

Data saturation is misunderstood in qualitative research. Learn what it actually means, code vs meaning saturation, and practical guidance for your study.

Framework analysis is the standard qualitative method for applied and policy research. This guide covers all 5 steps with worked examples and when to use it.

Qualitative data collection includes interviews, focus groups, observation, and more. This guide compares 8 methods on depth, feasibility, and analysis needs.

How to code interview transcripts step by step: build a codebook, apply codes consistently, cluster into themes, check reliability, and scale with AI.

CAQDAS is qualitative data analysis software for coding and managing research data. Learn its history, the 3 generations, and how AI is changing QDA software.

How to code qualitative interviews with AI: why chatbots summarise instead of coding, how systematic AI coding works, and how to export to NVivo via REFI-QDA.

A 2026 look at the strengths and weaknesses of qualitative research — depth vs generalisability, cost, bias, and how AI is changing the cost-benefit calculation.

By the end of this guide, you'll know thematic analysis's 6 phases, how to code qualitative data, and the 3 most common mistakes that lead reviewers to reject findings. With worked examples.