1/20
Read
30 min?
W03
Monday
Craft
NIST/SEMATECH e-Handbook of Statistical Methods
Monday build block
The public, citable reference for the limits you compute on Monday. Phase I vs Phase II is the distinction that stops you fooling yourself
Read exactly: 6.3.4 What are multivariate control charts? → 6.5.4.3 Hotelling's T² → 6.5.4.3.6 Constructing multivariate charts
Produce: The limit formula, with its source URL, in a comment above the code that implements it
In: LABLOOP-W03 Notebook
2/20
Read
30 min?
W03
Monday
Craft
NIST/SEMATECH e-Handbook ch. 6.5 "Tutorials: multivariate control charts"
Monday build block
· after NIST/SEMATECH e-Handbook of Statistical Methods
· Read it inside Monday's build block
Build-block reading · NIST/SEMATECH e-Handbook ch. 6.5 "Tutorials: multivariate control charts" — https://www.itl.nist.gov/div898/handbook/pmc/section3/pmc34.htm (sections 6.3.4 and 6.5.4.3)
In: LABLOOP-W03 Notebook
3/20
Read
30 min?
W03
Tuesday
Craft
OpenStax Microbiology, ch. 9 "Microbial Growth"
Tuesday · B3
You will discover your week-01 Monod model already explains the log phase — and what it does not explain
Read exactly: The growth-curve section only (lag, log, stationary, death). Oxygen, temperature and pH are parked
Produce: notes/bio/B3.md + a hand-drawn growth curve photographed into the notes
In: LABLOOP-W03 Notebook
4/20
Read
30 min?
W03
Wednesday
Craft
erdogant/pca README
Wednesday build block
A second implementation to compare against. Compare numbers, never copy them without understanding
Read exactly: The Hotelling T² / SPE outlier section
Produce: One line in review.md: do your limits agree with theirs, and if not, why
In: LABLOOP-W03 Notebook
6/20
Watch
7 min
W03
Thursday
Craft
StatQuest · "Machine Learning Fundamentals: Bias and Variance"
Thursday · M3
· after 3Blue1Brown · "Eigenvectors and eigenvalues"
· Thursday, after V4
Produce: The bias-variance sentence in notes/ml/M3.md
In: LABLOOP-W03 Notebook
7/20
Watch
13 min
W03
Thursday
Craft
StatQuest · "Linear Regression, Clearly Explained!!!"
Thursday · M3
· after StatQuest · "Machine Learning Fundamentals: Bias and Variance"
· Thursday, after V2
Produce: One regression fitted on two IndPenSim variables and read aloud: slope, intercept, what it means
In: LABLOOP-W03 Notebook
8/20
Watch
15 min?
W03
Saturday
Sandbox
optional
ISLP
Saturday sandbox
ISLP ch. 2 and 3.1-3.3 — statlearning.com (free PDF) + the matching Stanford Statistical Learning with Python videos. Moved out of core on 2026-09-29
In: LABLOOP-W03 Notebook
9/20
Read
30 min?
W03
Saturday
Sandbox
optional
Nomikos & MacGregor (1995), "Multivariate SPC charts for monitoring batch processes"
Saturday sandbox
· after ISLP
Nomikos & MacGregor (1995), "Multivariate SPC charts for monitoring batch processes", Technometrics 37(1):41-59 — the founding paper of batch MSPC. Read abstract + figures
In: LABLOOP-W03 Notebook
10/20
Read
30 min?
W03
Saturday
Sandbox
optional
Kourti & MacGregor (1995), "Process analysis, monitoring and diagnosis, using multivariate proje…
Saturday sandbox
· after Nomikos & MacGregor (1995), "Multivariate SPC charts for monitoring batch processes"
Kourti & MacGregor (1995), "Process analysis, monitoring and diagnosis, using multivariate projection methods", Chemometrics and Intelligent Laboratory Systems 28:3-21 (verify)
In: LABLOOP-W03 Notebook
11/20
Watch
15 min?
W03
Saturday
Sandbox
optional
Crash Course Statistics
Saturday sandbox
· after Kourti & MacGregor (1995), "Process analysis, monitoring and diagnosis, using multivariate proje…
Crash Course Statistics (YouTube), episodes on the normal distribution and control charts' ancestor, the z-score
In: LABLOOP-W03 Notebook
12/20
Read
30 min?
W03
Saturday
Sandbox
optional
James, Witten, Hastie, Tibshirani & Taylor, An Introduction to Statistical Learning with Applica…
Saturday sandbox
· after Crash Course Statistics
James, Witten, Hastie, Tibshirani & Taylor, An Introduction to Statistical Learning with Applications in Python — free PDF at statlearning.com — Ch. 2 (whole) and 3.1-3.3 only. Moved out of core on 2026-09-29
In: LABLOOP-W03 Notebook
13/20
Watch
15 min?
W03
Saturday
Sandbox
optional
Stanford Online · Statistical Learning with Python
Saturday sandbox
· after James, Witten, Hastie, Tibshirani & Taylor, An Introduction to Statistical Learning with Applica…
Stanford Online · Statistical Learning with Python (Hastie, Tibshirani et al.) — Playlist: youtube.com/playlist?list=PLoROMvodv4rPP6braWoRt5UCXYZ71GZIQ · course page: online.stanford.edu/courses/sohs-ystatslearningp-statistical-learning-python. Moved out of core on 2026-09-29
In: LABLOOP-W03 Notebook
14/20
Run
30 min?
W03
Saturday
Sandbox
optional
Nomikos P. & MacGregor J.F., "Multivariate SPC Charts for Monitoring Batch Processes", Technomet…
Saturday sandbox
· after Stanford Online · Statistical Learning with Python
Nomikos P. & MacGregor J.F., "Multivariate SPC Charts for Monitoring Batch Processes", Technometrics 37(1):41-59, 1995. DOI 10.1080/00401706.1995.10485888 · author PDF mirror: three-mode.leidenuniv.nl/pdf/n/nomikosmacgregor1995tmet.pdf. The founding paper of batch MSPC — abstract and figures are enough. Cite it in week 08's report
In: LABLOOP-W03 Notebook
15/20
Read
30 min?
W03
Saturday
Sandbox
optional
Kourti T. & MacGregor J.F., "Process analysis, monitoring and diagnosis, using multivariate proj…
Saturday sandbox
· after Nomikos P. & MacGregor J.F., "Multivariate SPC Charts for Monitoring Batch Processes", Technomet…
Kourti T. & MacGregor J.F., "Process analysis, monitoring and diagnosis, using multivariate projection methods", Chemometrics and Intelligent Laboratory Systems 28:3-21, 1995. (verify)
In: LABLOOP-W03 Notebook
16/20
Run
30 min?
W03
Saturday
Sandbox
optional
salvadorgarciamunoz/pyphi
Saturday sandbox
· after Kourti T. & MacGregor J.F., "Process analysis, monitoring and diagnosis, using multivariate proj…
salvadorgarciamunoz/pyphi — a pharma practitioner's PCA/PLS with T² and SPE. Niche, but written by someone who does this for a living
In: LABLOOP-W03 Notebook
17/20
Read
30 min?
W03
Saturday
Sandbox
optional
Coursera Introduction to Statistics
Saturday sandbox
· after salvadorgarciamunoz/pyphi
Coursera Introduction to Statistics (Stanford, Walther), regression module — coursera.org/learn/stanford-statistics, free audit. Only if ISLP ch. 3 feels steep
In: LABLOOP-W03 Notebook
18/20
Run
30 min
W03
Build
intro-stat-learning/ISLP_labs
Colab: Ch02-statlearn-lab.ipynb, then Ch03-linreg-lab.ipynb; redo the regression on two IndPenSim variables
In: LABLOOP-W03 Notebook
19/20
Run
30 min
W03
Build
erdogant/pca
Its README shows Hotelling T² and SPE outlier detection on top of PCA; run the example, then compare its limits with yours (never ship its numbers without understanding them)
In: LABLOOP-W03 Notebook
20/20
Run
30 min
W03
Build
statsmodels/statsmodels
Fit an OLS on two variables and read the summary table line by line with ISLP ch. 3 open
In: LABLOOP-W03 Notebook