Statistics for researchers — module 1, with worked datasets
Designing an experiment that can answer the question, choosing the test, and reporting uncertainty in a way reviewers accept.
Pillar four
The skills that sit between a degree and a working research career — taught in short, practical modules with the data files included so you can follow along rather than watch.
What this covers
Every course ships with a downloadable workbook, the raw data used in the examples, and a written guide for people who would rather read than watch.
The physical and chemical groundwork that specialist courses assume you already have — revisited properly, with worked examples.
What each technique measures, what it cannot tell you, and how to read the output without over-claiming. SEM, XRD, spectroscopy and thermal analysis.
Designing an experiment that can answer the question, choosing the right test, and reporting uncertainty in a way reviewers accept.
Python, R and MATLAB taught against real research tasks — data cleaning, fitting, plotting and making the analysis reproducible.
Literature review, research design, ethics, data management and writing — the process skills that decide whether the work gets finished.
Course materials
Every course ships with the files used in the examples, so you can follow along instead of watching.
Four exercises against the example dataset, with worked answers: what counts as n, choosing a paired test, reading a confounded design, and writing a caption that survives review.
Sample file Sign in to downloador registerA complete 13-page issue with all five standing sections, produced as the layout specification for the magazine and as a test document for the reader. Every word in it is placeholder.
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New modules, short courses and recordings. Anything with a video carries a link straight to it.
Designing an experiment that can answer the question, choosing the test, and reporting uncertainty in a way reviewers accept.
Resolution, colour mode and the four things that get a figure sent back. Two hours, with the files used in the examples.
One module from each course is open without an account, workbook included, so you can judge the teaching before you commit.
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