[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_29":-5,"_39":-5,"_40":41,"_42":43,"_44":45,"_46":47,"_48":49,"_50":51,"_52":53,"_54":55,"_56":57,"_58":59},"routes/_store+/_readers+/email_author.$slug/route",{"_9":10,"_11":-5,"_12":-5},"book",{"_13":14,"_15":16,"_17":18,"_19":20,"_21":22,"_23":24},"currentUser","formToken","id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvODQ1Nzk","title","Data Exploration and Visualisation with R: From Data Quality to Credible Evidence","state","published","contactAuthorMethod","email","aboutText","

Good data lead to better questions, deeper understanding, and more credible evidence.

Data Exploration and Visualisation with R: From Data Quality to Credible Evidence is a practical guide to understanding data before drawing conclusions from them. Rather than treating visualisation as a final decorative step, the book places it at the centre of statistical reasoning—using plots to investigate data quality, reveal structure, challenge assumptions, and communicate findings responsibly.

Beginning with the processes through which data are generated, measured, recorded, and prepared, the book develops a thoughtful approach to exploratory analysis. It moves from distributions and relationships to missing data, outliers and robust methods, causal reasoning with DAGs, geospatial exploration, dimensionality reduction, and temporal data. Throughout, R is used not merely to produce graphics, but to support reproducible investigation and critical interpretation.

The emphasis is always on asking the right questions: What does this pattern show? What might explain it? What could mislead us? What does the evidence actually support? Connections to data science, machine learning, and AI show why these habits matter well beyond traditional statistical analysis.

Written for students, researchers, and data professionals, this book aims to develop the judgment needed to move from raw and imperfect observations to visualisations—and conclusions—that can withstand scrutiny.

Better data. Clearer questions. More credible evidence.

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Kick off your book project, get started with GhostAI, get better at marketing, or spend the day doing all three! Free live workshops on Zoom. Saturday, June 27, 2026.

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