Your students already have
a research computer
in their pocket.
Every research-methods course confronts the same wall: statistical software costs more than the textbook, installs badly, only runs on the computer it’s licensed to, and teaches students they need permission to touch data. PsyStat Lab is 240+ methods, an AI teaching assistant, and a validated numerical core — usable from any phone, tablet, or browser, without an install, on the first day of class.
The status quo, priced honestly
These are what your department is already paying — per student, per year, for tools designed in an era before mobile.
Per user per year at academic rates. IBM’s public rack rate. Doesn’t include install support, and students lose access the day they graduate.
Six-month student rate. Undergraduate methods courses can’t justify it, so instructors teach around the tool rather than with it.
The consistent finding when methods instructors are surveyed: the first two to three weeks of any hands-on stats course are absorbed by installation, licensing, and platform troubleshooting instead of statistics.
What changes with a mobile-first tool
Not just a cost swap. A different pedagogy.
Class runs the first day
Students open a browser or the app. There is nothing to install, nothing to license, nothing to configure. The two-week install triage disappears. You get those weeks back for actual statistics.
Homework in bed. Lab work at the bench.
PsyStat runs identically on phone, tablet, laptop, and computer-lab desktop. Students who commute do assignments on the bus. Students in field settings run analyses on real data on tablets. Students who never touch a “real computer” are no longer excluded.
Every student has a TA
The AI advisor explains why a test was selected, flags assumption violations, and walks a stuck student through their data at 2 a.m. It does not do the assignment for them — it teaches the reasoning your syllabus is already trying to build.
Numbers you can defend
Every method PsyStat exposes is compared against a canonical reference (NIST StRD, R, or peer-reviewed textbook) on every commit. See the public validation report. When a student cites PsyStat in a paper, the citation is bound to a specific build and a specific validation snapshot.
Syllabus-ready module map
A standard 12-week undergraduate research-methods sequence, mapped to the PsyStat modules that cover each week. Copy this into your syllabus; every module link goes straight to the tool.
| Week | Topic | PsyStat modules & tools |
|---|---|---|
| 1 | Research questions & measurement Formulating testable hypotheses, operationalization, reliability and validity in the abstract. |
Study Planner, Research Hub. Simulation: What does reliability look like? Interactive noise-signal demo.
|
| 2 | Descriptive statistics & visualization Means, medians, spread, distributional shape. Reading a graph before running a test. |
Stats Studio → Descriptive, Data Cleaning. Interactive histogram + boxplot builder.
|
| 3 | Sampling & the CLT Sampling distributions, standard errors, the Central Limit Theorem, why sample size matters. | Simulation: Sampling distributions. Draws thousands of samples on the phone in real time so students see the CLT emerge instead of taking it on faith. |
| 4 | Hypothesis testing intuition Null vs. alternative, alpha, Type I/II errors, power. |
Power Analysis, simulation: Type I vs. Type II tradeoffs. Students find the alpha level themselves.
|
| 5 | Comparing two groups: t-tests Independent-samples, paired, Welch’s correction, effect sizes. |
Stats Studio → t-test. Assignment: run indep + paired on the built-in Rosner and Snedecor teaching datasets. Validated against the golden-number suite.
|
| 6 | ANOVA: three or more groups One-way, factorial, post-hoc procedures, eta-squared. |
Stats Studio → ANOVA. Tukey HSD auto-generated. Assumption-check dashboard flags violations before the student misinterprets output.
|
| 7 | Correlation & regression Pearson, Spearman, Kendall, simple linear regression, coefficient interpretation. |
Stats Studio → Correlation / Regression. NIST-Norris-validated OLS. Interactive residual plots.
|
| 8 | Chi-square & categorical data Contingency tables, Cramer’s V, odds ratios. |
Stats Studio → Chi-square. 2x2 tables with OR + Fisher’s exact fallback for small counts.
|
| 9 | Non-parametric alternatives When assumptions fail. Mann-Whitney, Wilcoxon signed-rank, Kruskal-Wallis. |
Advanced Stats → Non-parametric. Same UI as t-test — students see the parallel structure.
|
| 10 | Reproducibility, pre-registration & open science The replication crisis, HARKing, pre-registration mechanics. |
Research Hub → Pre-Registration Builder (OSF and AsPredicted formats). Replication Package export. Encyclopedia entry on the replication crisis.
|
| 11 | Multiverse & specification-curve analysis The p-hacking problem made concrete. What robust findings actually look like. |
Multiverse Analysis. Students see how a “significant” finding changes across analytic choices. Best intuition-builder for critical reading.
|
| 12 | Communicating results APA-formatted reporting, figures, effect sizes, honest caveats. |
APA Formatter, Narrative Builder, Slides Export. Every analysis produces publication-shape output automatically — students learn to write results by editing structured drafts, not from a blank page.
|
This map matches the outline of Psychological Research Methods (Bordens & Abbott, 2018) and Statistical Methods for the Behavioral Sciences (Gravetter et al., 2020) — adjust week numbers to your semester. A downloadable syllabus insert (PDF + editable DOCX) is included in every pilot.
Run a full semester on us
The first 20 methods courses to pilot PsyStat Lab receive a full semester of Classroom-tier access at no cost, for the instructor plus every enrolled student. In exchange, we ask for:
- Two 30-minute check-ins during the semester (mid-term and end-of-semester feedback)
- Permission to reference your course (if you’re willing) in future case studies — opt-in only, we won’t quote you without written approval
- Honest feedback on what worked, what didn’t, and what students actually used
We are not a large team. Every pilot instructor gets a direct line to the person building the tool, and requests routinely turn into shipped features within a semester.
Or email moonlit-social-labs@proton.me directly. Please include your institution, course title, expected enrollment, and semester.
Instructor FAQ
Concrete answers to the questions instructors have actually asked. If you have one that isn’t here, email us and it’ll appear on this page.