Statistics is often framed as a gatekeeping barrier to understanding. This module reframes it as meaning-making: a set of tools that help you interpret patterns, ask better questions, and communicate findings with care.

You begin by exploring how to choose methods that align with your research question rather than defaulting to familiar tests. You learn how assumptions shape statistical choices and how to select approaches that honour the structure of your data.

The module then guides you into responsible interpretation. You explore how to read effect sizes, confidence intervals, and model outputs in ways that reflect nuance rather than certainty. You learn how to avoid overstating significance and how to communicate results in language that is accurate, accessible, and grounded.

Ethics is woven throughout. You reflect on how statistical decisions influence whose experiences are represented, how missing data is handled, and how conclusions shape real‑world narratives. You explore how to use statistics in ways that illuminate rather than distort.

By the end, statistics feels less like a hurdle and more like a relational tool, one that supports understanding, transparency, and integrity.

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