aimnova.
DashboardMy LearningPaper MasteryStudy Plan

Stay in the loop

Study tips, product updates, and early access to new features.

aimnova.

AI-powered IB study platform with personalised plans, instant feedback, and examiner-style marking.

IB Subjects

  • IB Diploma
  • All IB Subjects
  • IB ESS
  • IB Business Management
  • IB Economics
  • IB Math AI SL
  • IB Math AA SL
  • Grade Calculator
  • Exam Timetable 2026
  • ESS Predictions
  • BM Predictions
  • IB Economics Predictions 2026

Study Resources

  • Free Study Notes
  • Revision Guide
  • Flashcards
  • ESS Question Bank
  • BM Question Bank
  • Mock Exams
  • Past Paper Feedback
  • Exam Skills
  • Command Terms

Company

  • Features
  • Pricing
  • About Us
  • Blog
  • Contact
  • Terms
  • Privacy
  • Cookies

© 2026 Aimnova. All rights reserved.

Made with 💜 for IB students worldwide

v0.1.644
NotesMath AA SLTopic 4.9
Unit 4 · Statistics & Probability · Topic 4.9

IB Math AA SL — Normal distribution

Topic 4.9 of IB Mathematics: Analysis and Approaches covers Normal distribution, which is part of Unit 4: Statistics & Probability. Students explore key concepts including Normal probabilities, The normal curve. A strong understanding of normal distribution is essential for IB Math AA SL exams and builds the foundation for connected topics across the syllabus.

Exam technique guidePractice questions

Key concepts in Normal distribution

Key Idea: The normal distribution models data that clusters symmetrically around an average — heights, masses, exam marks. On Paper 2 you read probabilities straight off the GDC; on Paper 1 you use symmetry and the 68–95–99.7 rule.

🔔 The model: X ~ N(μ, σ²)

X∼N(μ, σ2)X \sim N(\mu,\ \sigma^{2})X∼N(μ, σ2)
μ\muμ
the mean — the centre of the bell
σ2\sigma^{2}σ2
the variance (the second number) — take √ to get σ
σ\sigmaσ
the standard deviation — sets the width
The bell is symmetric about μ, so the mean = median = mode. The total area is 1, and 0.5 lies on each side of the mean. Probabilities are areas under the curve.

💻 Finding P(a < X < b) — Paper 2

Without a calculator: P(X < μ) = 0.5, and about 68% of data lies within 1σ of the mean, 95% within 2σ, and 99.7% within 3σ. The leftover splits into two equal tails — e.g. outside 1σ is 0.32, so each tail is 0.16.

✏️ IB-style worked examples

IB-style question — a probability and an expected number (Paper 2)

The masses of oranges are modelled by X ~ N(180, 15²) grams. An orange is rejected if it is lighter than 160 g. (a) Find P(X < 160). (b) In a crate of 500 oranges, find the expected number rejected.

Step by step:

  1. The second number is the variance, so σ = √225 = 15.

    X∼N(180, 152)X \sim N(180,\ 15^{2})X∼N(180, 152)
  2. P(X < 160): lower bound −1ᴇ99, upper 160.

    P(X<160)=normalcdf(−1E99, 160, 180, 15)≈0.0912P(X < 160) = \text{normalcdf}(-1\text{E}99,\ 160,\ 180,\ 15) \approx 0.0912P(X<160)=normalcdf(−1E99, 160, 180, 15)≈0.0912
  3. Expected number = probability × total.

    500×0.0912≈46500 \times 0.0912 \approx 46500×0.0912≈46
Final answer:

(a) P(X < 160) ≈ 0.0912. (b) About 46 oranges are expected to be rejected.

IB-style question — symmetry and comparing curves (Paper 1)

Two classes sit the same test. Both sets of marks are normal with mean 62, but class A has σ = 5 and class B has σ = 12. (a) Write down P(mark > 62) for class A. (b) Whose marks are more consistent, and what does the curve look like?

Step by step:

  1. 62 is the mean, and the curve is symmetric about it.

    P(mark>62)=0.5P(\text{mark} > 62) = 0.5P(mark>62)=0.5
  2. Smaller σ means less spread — taller and narrower.

    σA=5<σB=12\sigma_A = 5 < \sigma_B = 12σA​=5<σB​=12
Final answer:

(a) P(mark > 62) = 0.5 (no calculator needed). (b) Class A is more consistent; its curve is taller and narrower.

Important: N(μ, σ²) gives the variance as the second number. normalcdf wants σ, so for N(180, 225) you must enter σ = √225 = 15, not 225. When the bracket already shows a square — N(180, 15²) — the σ is the 15.

Tap each card to reveal the answer.

Exam Tips

  • N(μ, σ²): the second number is the variance — enter σ = √variance into the GDC.
  • normalcdf needs a lower AND an upper bound; use −1ᴇ99 / 1ᴇ99 for a one-sided tail.
  • Anything asked at the mean is 0.5 — by symmetry, no calculator needed.
  • Expected number = (normalcdf probability) × total — show both, each earns a mark.
  • Sketch the bell, mark μ, and shade the region to sanity-check your probability.

What you'll learn in Topic 4.9

  • 4.9.1 Normal probabilities
  • 4.9.2 The normal curve
Suggested study order: Read the notes for each sub-topic below → test yourself with flashcards → attempt practice questions → review exam technique.

Study resources — 4.9 Normal distribution

4.9.1

Normal probabilities

Notes
4.9.2

The normal curve

Notes

Ready to study Normal distribution?

Get AI-powered practice questions, personalised feedback, and a study planner tailored to your IB Math AA SL exam date.

Start studying free

Topic 4.9 Normal distribution forms a core part of Unit 4: Statistics & Probability in IB Math AA SL. Mastering these concepts will strengthen your understanding of connected topics across the syllabus and prepare you for exam questions that require analysis, evaluation, and real-world application.

Previous topic
4.8 Binomial distribution
Next topic
4.10 Regression & prediction
All Math AA SL topics
Exam technique

Ready to practice?

Get AI-graded practice questions, mock exams, flashcards, and a personalised study plan — all aligned to your IB syllabus.

Start Studying Free

No credit card required · Cancel anytime