Applied Statistics with Python and R

NEKpress Research: Proof-First Guides

*From Question to Defensible Result through Reproducible Analysis,

Cross-Language Verification, and APA-Style Reporting*

Python for the workflow. R for verification. PyStatsV1 for the bridge.

This is the official companion page for Book 1. The current executable

companion is Companion v0.2.1, delivered by PyStatsV1 0.25.2. The

resources use synthetic teaching data. No account, no payment card, and no DRM are required.

Use the current launcher and Companion v0.2.1 with this edition. The older

Psych Stats with Python starter kit and Companion v0.1 archive remain

available only for historical readers; they are not interchangeable with the

current book's commands, figures, design contract, or receipts.

Official Book 1 companion

The easiest supported route is the released PyPI launcher:

python -m pip install "pystatsv1[book1]==0.25.2"
pystatsv1 book1 init
cd psych_stats_with_python_companion_v0_2_1
pystatsv1 book1 verify --dest .
python -m pip install -r requirements-book1-companion.txt
make design-audit
make figures

PyStatsV1 0.25.2 creates Companion v0.2.1 locally. The launcher records the

versioned source identity; it does not upload data, select a statistical method,

or replace an analysis plan.

Direct ZIP fallback

The direct ZIP is byte-for-byte identical to the released Companion v0.2.1

asset carried by PyStatsV1 0.25.2. Verify the sidecar before extraction, then

run pystatsv1 book1 verify --dest . inside the extracted folder.

What the companion contains

synthetic CSV files for the Book 1 methods;
visible Python scripts using pandas, SciPy, and statsmodels;
optional independent base-R checks;
JSON result records and chapter-level parity receipts;
six reproducible Matplotlib figures;
a deterministic design contract; and
source maps and maintenance receipts for the reported teaching examples.

The companion is a local teaching workflow. It does not accept real-data uploads,

select a statistical method, or make publication decisions; it is not a data-upload service

or a one-click paper generator.

What each verification command establishes

pystatsv1 book1 verify --dest . checks whether extracted source files match

the packaged bundle manifest.

make design-audit checks the documented row structure, identifiers, factor

levels, repeated observations, and analysis, figure, and reporting bindings.

make figures regenerates the six declared teaching figures.
make all, when Rscript is installed, runs the Python analyses,

independent R verification, and declared parity comparisons.

These are bounded reproducibility checks, not universal validation. They do not

by themselves establish measurement validity, ethical authorization, assumption adequacy, causal

identification, practical importance, or generalizability.

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.

APA Article Lab capstone

Read the guide. Run the synthetic lab. Work with a statistician when your real project needs judgment.

The APA Article Lab is a synthetic psychology teaching workflow and the free

capstone path for readers who have learned the Book 1 foundations. It generates

the example data, performs a documented Python analysis, verifies selected

results in R, records a Python/R parity receipt, and creates APA-style DOCX/PDF

teaching artifacts.

The lab demonstrates a reproducible teaching workflow. It does not guarantee

journal acceptance, universal submission suitability, or a defensible analysis

for an unrelated real dataset.

Find Before You Hire a Statistician at NEKpress.ca.

The guide helps readers clarify a question, prepare materials, define scope,

protect sensitive data, and recognize when professional judgment is needed.

It is decision-oriented; the Book 1 companion and APA Article Lab are

hands-on synthetic workflows.

Historical archives

Historical Companion v0.1 archive

The older Psych Stats with Python starter kit and Companion v0.1 archive

remain available as a shorter Python-first warm-up for historical readers. They

use synthetic data only. They are not interchangeable with the

current book's commands, figures, design contract, or receipts.

Synthetic-data and ethics boundary

Do not place identifiable participant data, credentials, restricted research

files, or sensitive exports in the public repository or downloadable lab. Real

coursework, thesis, lab, consulting, and journal work remain subject to the

relevant instructor, advisor, ethics, institutional, data-governance, and

publisher requirements.

Payment and consulting boundary

This page does not use Stripe checkout. Free resources remain separate from the

optional sandbox contribution infrastructure. This page does not sell consulting, promise journal acceptance, or replace research supervision.