Analyzing Research Data
Like Duolingo, but for Analyzing Research Data. Tomo turns the whole topic into a game you play five minutes a day, until it actually sticks.
For the part of you with thirty open tabs that never became anything.
21 levels across 3 sections, about 42 minutes end to end, roughly 8 days at five minutes a day. It moves through Critical Deconstruction, The Mechanics of Rigor, and Synthesis and Ethics.
Free forever · No credit card · iPhone & Android
Key ideas in Analyzing Research Data
- Abstracts prioritize headline results
- Significance vs Generalizability
- Marketing terms vs Proxies
- Logic chain breaks
- Ease of capture vs Alignment
- Identifying proxy drift
- Evaluating abstract claims
- Logic chain and proxies
- Pre-registration locks the hypothesis and analysis plan to prevent 'HARKing'
- Exploratory data mining is for hypothesis generation, while confirmatory research requires a fixed protocol
- Evaluating the reliability of an abstract's claims
- Post-hoc adjustments to variables in a confirmatory study invalidate the resulting p-values
- The choice of a specific 'fairness metric' often mathematically precludes certain results
- Identifying breaks in the logic chain between research questions and data proxies
- Assumptions about 'missingness' can artificially inflate performance metrics
- The baseline comparison may have been intentionally under-tuned
You've tried the other tabs
Thirty open tabs. Four facts you actually kept.
You watched. You nodded. By Sunday it was gone.
One answer, then back to scrolling.
Eight weeks. You meant to finish. You didn't.
Tomo gives Analyzing Research Data the Duolingo treatment: levels, streaks, and quick quizzes that test what you just learned. That game loop is what the tabs above never had, so it's the one you actually finish.
Here's what playing it feels like
A real question from this course. Take your best guess.
When an abstract claims a result is 'highly significant,' what is it most likely referring to mathematically?
Get it right to open this lesson and 20 more in the app.
Where Analyzing Research Data takes you
Move beyond basic statistics to critically evaluate the methodology, rigor, and causal claims of modern research papers.
- 1
Critical Deconstruction
- Dissecting the Research Paper
- Identifying Sampling and Selection Bias
- 2
The Mechanics of Rigor
- Significance, Effect Size, and Power
- The Reproducibility Crisis and P-Hacking
- Causal Inference and Natural Experiments
- 3
Synthesis and Ethics
- Algorithmic Fairness and Data Ethics
- Meta-Analysis and Communication
3 sections · 7 units · 21 levels. Built to play, not to enroll.
You pick the voice
Analyzing Research Data is taught in the The Professor style: clear, structured, thorough. Want a different feel? In the app you can spin up the same topic in any of Tomo's teaching styles. Same facts, totally different vibe.
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Start Analyzing Research Data today.
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