# Week 03 — Materials: what to read, what to watch

Status: PREPARED 2026-09-15. Links checked on 2026-09-15 unless marked **(verify)**.
Authority: v6 master plan, Week 3 "Learn it" block (units **B3** microbial growth, **M3** ISLP ch. 2-3), expanded into exact locators per the [source contract](../../SOURCES.md).

[Week 03 brief](./specs.md) · [Commitment](./commitment.md) · [Evidence](./evidence.md) · [Review](./review.md) · [Previous](../week-02-indpensim-data-and-baseline/materials.md) · [Next](../week-04-batchlens-first-release/materials.md)

## Where this fits in the week

| Slot | Budget | Material |
|---|---:|---|
| **Monday build block** | 20 min max | R3 NIST handbook, the three pages named below. Read it **while** writing the T² code, not before |
| **Tuesday · B3** | 45 min | R1 growth-curve section (30) → draw the curve by hand (15). The rest of the block is build |
| **Wednesday build block** | 10 min | R4 `erdogant/pca` README, to sanity-check your limits against someone else's |
| **Thursday · M3** | 60 min + 30 | V4 eigenvectors (17) → V2 (7) → V1 (13) → one regression on two IndPenSim variables (~20); last 30 min founder paper |
| **Saturday sandbox** | optional | "Deeper", after catch-up |

Hard rule for this week: **limits are computed from the normal batches, never typed in.** Every source below is there to defend that sentence.

## Read

| # | Source | Exact scope | Min | Why this week | Produce |
|---|---|---|---:|---|---|
| R1 | OpenStax *Microbiology*, ch. 9 "Microbial Growth" — [9-introduction](https://openstax.org/books/microbiology/pages/9-introduction), summary at [9-summary](https://openstax.org/books/microbiology/pages/9-summary) | The growth-curve section only (lag, log, stationary, death). Oxygen, temperature and pH are parked | 30 | You will discover your week-01 Monod model already explains the log phase — and what it does *not* explain | `notes/bio/B3.md` + a **hand-drawn** growth curve photographed into the notes |
| R3 | NIST/SEMATECH *e-Handbook of Statistical Methods*, ch. 6 | [6.3.4 What are multivariate control charts?](https://www.itl.nist.gov/div898/handbook/pmc/section3/pmc34.htm) → [6.5.4.3 Hotelling's T²](https://www.itl.nist.gov/div898/handbook/pmc/section5/pmc543.htm) → [6.5.4.3.6 Constructing multivariate charts](https://www.itl.nist.gov/div898/handbook/pmc/section5/pmc5436.htm) | 20 | The public, citable reference for the limits you compute on Monday. Phase I vs Phase II is the distinction that stops you fooling yourself | The limit formula, with its source URL, in a comment above the code that implements it |
| R4 | [erdogant/pca](https://github.com/erdogant/pca) README | The Hotelling T² / SPE outlier section | 10 | A second implementation to compare against. Compare numbers, never copy them without understanding | One line in `review.md`: do your limits agree with theirs, and if not, why |

## Watch (YouTube)

| # | Channel · title | ~Length | Link | When | Produce |
|---|---|---:|---|---|---|
| V1 | StatQuest · "Linear Regression, Clearly Explained!!!" | ~13 min | [youtube.com/watch?v=7ArmBVF2dCs](https://www.youtube.com/watch?v=7ArmBVF2dCs) | Thursday, after V2 | One regression fitted on two IndPenSim variables and read aloud: slope, intercept, what it means |
| V2 | StatQuest · "Machine Learning Fundamentals: Bias and Variance" | ~7 min | [youtube.com/watch?v=EuBBz3bI-aA](https://www.youtube.com/watch?v=EuBBz3bI-aA) | Thursday, after V4 | The bias-variance sentence in `notes/ml/M3.md` |
| V4 | 3Blue1Brown · "Eigenvectors and eigenvalues" (*Essence of Linear Algebra* ch. 14) | ~17 min | [youtube.com/watch?v=PFDu9oVAE-g](https://www.youtube.com/watch?v=PFDu9oVAE-g) **(verify)** | Thursday, first | One sentence in `notes/ml/M3.md`: what last Friday's principal components actually are |
## Deeper — Saturday sandbox only

- James, Witten, Hastie, Tibshirani & Taylor, *An Introduction to Statistical Learning with Applications in Python* — free PDF at [statlearning.com](https://www.statlearning.com/) — Ch. 2 (whole) and **3.1-3.3** only. Moved out of core on 2026-09-29.
- Stanford Online · *Statistical Learning with Python* (Hastie, Tibshirani et al.) — Playlist: [youtube.com/playlist?list=PLoROMvodv4rPP6braWoRt5UCXYZ71GZIQ](https://www.youtube.com/playlist?list=PLoROMvodv4rPP6braWoRt5UCXYZ71GZIQ) · course page: [online.stanford.edu/courses/sohs-ystatslearningp-statistical-learning-python](https://online.stanford.edu/courses/sohs-ystatslearningp-statistical-learning-python). Moved out of core on 2026-09-29.
- Nomikos P. & MacGregor J.F., "Multivariate SPC Charts for Monitoring Batch Processes", *Technometrics* 37(1):41-59, 1995. DOI [10.1080/00401706.1995.10485888](https://doi.org/10.1080/00401706.1995.10485888) · author PDF mirror: [three-mode.leidenuniv.nl/pdf/n/nomikosmacgregor1995tmet.pdf](https://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.
- Kourti T. & MacGregor J.F., "Process analysis, monitoring and diagnosis, using multivariate projection methods", *Chemometrics and Intelligent Laboratory Systems* 28:3-21, 1995. **(verify)**
- [salvadorgarciamunoz/pyphi](https://github.com/salvadorgarciamunoz/pyphi) — a pharma practitioner's PCA/PLS with T² and SPE. Niche, but written by someone who does this for a living.
- Coursera *Introduction to Statistics* (Stanford, Walther), regression module — [coursera.org/learn/stanford-statistics](https://www.coursera.org/learn/stanford-statistics), free audit. Only if ISLP ch. 3 feels steep.

## Link check log — 2026-09-15

- Verified today: R1 (both pages), R3 (all three NIST pages), V1, V2, V3 playlist and Stanford course page, Nomikos & MacGregor DOI and PDF mirror.
- Not re-checked today: R2 statlearning.com (verified 2026-09-12, see SOURCES.md), R4, pyphi, Kourti & MacGregor **(verify)**, Coursera statistics.
- Record in [`evidence.md`](./evidence.md) which NIST page each computed limit came from. A limit without a citation is a threshold someone typed.

## NotebookLM kit sources for `LABLOOP-W03`

(1) this file; (2) the Week 3 chapter from the v6 master; (3) R1 pages; (4) ISLP ch. 2-3 PDF; (5) V3 ch. 2 and ch. 3 video URLs; (6) the three NIST pages; (7) V1 and V2 URLs; (8) Nomikos & MacGregor abstract; (9) your T² plot description and computed limits as text; (10) [`QUESTIONS.md`](../../QUESTIONS.md).

Focus line: `Focus: from a golden batch anecdote to a statistical envelope; Hotelling T² and SPE as two different ways a batch can be abnormal; the bias-variance trade-off.`

Custom question: `Explain the difference between T² and SPE alarms using a portfolio-dashboard analogy, then tell me which of the two should fire first for a feed-pump failure and why.`