NIST e-Handbook
NIST e-Handbook ch. 5.1-5.3 — itl.nist.gov/div898/handbook (45 min)
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Penn State STAT 503 Design of Experiments online notes, lesson on randomised complete block desi…
Tuesday · after NIST e-Handbook
Penn State STAT 503 Design of Experiments online notes, lesson on randomised complete block designs — online.stat.psu.edu/stat503 (30 min)
In: LABLOOP-W25 Notebook
Michael Clark, Mixed Models with R
Saturday sandbox
Michael Clark, Mixed Models with R — m-clark.github.io/mixed-models-with-R (concepts transfer to Python)
In: LABLOOP-W25 Notebook
Bambi documentation
Saturday sandbox · after Michael Clark, Mixed Models with R
Bambi documentation (bambinos.github.io/bambi), Bayesian mixed models in one formula
In: LABLOOP-W25 Notebook
StatQuest on ANOVA and "Design matrices"
Saturday sandbox · after Bambi documentation
StatQuest on ANOVA and "Design matrices" (search in channel)
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Coursera Practical Time Series Analysis
Saturday sandbox · after StatQuest on ANOVA and "Design matrices"
Coursera Practical Time Series Analysis — only if a client's trials are longitudinal
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Piepho, Büchse & Emrich (2003), "A hitchhiker's guide to mixed models for randomized experiments"
Piepho, Büchse & Emrich (2003), "A hitchhiker's guide to mixed models for randomized experiments", Journal of Agronomy and Crop Science 189:310-322 (skim sections 1-3)
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statsmodels/statsmodels
MixedLM example from the docs (random intercept per block); then fit one agridat trial
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bambinos/bambi
Same trial as a Bayesian mixed model; compare intervals with MixedLM
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vincentarelbundock/Rdatasets
Pull 10 agridat CSVs by URL; this is your public data source
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567-labs/instructor
Spreadsheet header → schema mapping with a Pydantic model, as in FermLit
In: LABLOOP-W25 Notebook
m-clark/mixed-models-with-R
Read the "random intercepts" chapter for intuition
In: LABLOOP-W25 Notebook