Stats notes written by people who remember the confusion.
Annotated guides for intro stats, MBA probability, and Python output interpretation — the ones your professor forgot to write.
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📝 Margin note: When |z| > 1.96, your p-value is under 0.05 — reject H₀ at 95% confidence. That's it. That's the whole test.
z-scores measure distance from the mean in units of std deviation
σ is population std dev — use s when you only have sample data
n > 30 means CLT applies and z-test is valid
Written by Dr. Priya Nair, Chapter 3
Not AI. Not algorithms. Actual humans who remember struggling.
Every chapter is written and reviewed by someone who lived through the confusion first.
Dr. Priya Nair
PhD Biostatistics, Johns Hopkins
"I write every explanation assuming the reader is brilliant but has never seen this before. That's how I wish someone had taught me."
Why the Normal Distribution is Everywhere
The Central Limit Theorem is the reason stats works at all. It says: add enough random things together and you get a bell curve. Every time.
Marcus Webb
Former student, now stats tutor
"I failed stats twice. Then I rewrote every chapter until my roommate — a history major — could explain p-values back to me."
The p-value is NOT the probability your hypothesis is true
This is the most misunderstood sentence in all of statistics. Your p-value is the probability of your data given H₀ is true — not the other way around.
Yuki Tanaka
Senior Data Scientist, ex-Netflix
"I contributed the real-world examples because textbooks always use toy datasets. Your future boss will hand you messy, real data."
Reading a Regression Table from Python Output
The coef column tells you: if X goes up by 1, Y changes by this much. That's 80% of what your manager actually cares about.
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