Applied statistics you can inspect, reproduce, and explain.

LearnToProgram.ca is the free companion portal for *Applied Statistics with

Python and R* and related NEKpress proof-first resources. Start with a question,

make the data layout visible, run a transparent Python workflow, verify selected

results in R, and report only what the evidence supports.

Start with Book 1

The Book 1 companion contains synthetic CSV files, visible Python scripts,

optional base-R checks, JSON outputs, parity receipts, and six reproducible

figures. It is designed for learning and inspection. It does not accept real

data, choose a method for you, or authorize a research project.

Read the guide. Run the synthetic lab. The APA Article Lab is now available as the capstone route, but it is not a guarantee of journal acceptance.

A proof-first learning path

Learn the statistical idea and identify what one row represents.
Reproduce the versioned synthetic workflow.
Check source integrity, data layout, analysis bindings, and reportable values.
Adapt only with appropriate authorization, documentation, and judgment.

Read the proof-first method for the reasoning behind this

sequence.

Free resources

the Book 1 Executable Companion v0.2.1;
the APA Article Lab Reader Starter v0.10.2;
the Getting Started with PyStatsV1 PDF and HTML resource;
historical starter files for readers following earlier material; and
a download manifest with SHA-256 integrity information.

No account, no payment card, and no DRM are required for the free path.

Platform support

Ubuntu native and Windows 11 with WSL2 + Ubuntu are verified reader routes.

macOS remains an untested power-user adaptation route. Docker, Dev Containers,

VS Code, and cloud accounts are not required.

Keep real data outside the public teaching path

The downloadable materials use synthetic teaching data. Do not place

identifiable participant data, credentials, restricted exports, coursework,

thesis files, or client records in a public repository, issue tracker, AI tool,

or companion folder. Real projects remain subject to the relevant instructor,

advisor, ethics, institutional, data-governance, and publisher requirements.