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NotesMath AA HLTopic 4.9Normal probabilities
Back to Math AA HL Topics
4.9.15 min read

Normal probabilities (Math AA HL)

IB Mathematics: Analysis and Approaches • Unit 4

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Contents

  • The normal model
  • Finding probabilities (normalcdf)
  • Symmetry & the 68–95–99.7 rule
  • Expected number in context
A symmetric bell curve: A normal variable X ~ N(μ, σ²) has a bell-shaped graph symmetric about its mean μ.

The standard deviation σ sets the width.

Probabilities are areas under the curve, and the total area is 1.

The shaded area under the normal curve IS the probability — a left tail, a right tail, or a central region.

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IB-style question — read the parameters

The masses of apples are modelled by X ~ N(150, 20²) grams.

State the mean and standard deviation, and the value the distribution is symmetric about.

Step by step

  1. N(μ, σ²): first is the mean, second is the variance.
  2. Symmetric about the mean.

Final answer

Mean 150 g, standard deviation 20 g, symmetric about 150 g.

Second number is the variance: N(150, 20²) means σ = 20 (variance 400).

The GDC needs σ, so take the square root of the variance if you're given it.

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Area between a lower and upper bound: On Paper 2 use normalcdf(lower, upper, μ, σ).

For P(X < a) use a very small lower bound; for P(X > a) use a very large upper bound; for P(a < X < b) use both.

IB-style question — P(X < a)

X ~ N(50, 8²).

Find P(X < 60) and P(X > 60).

Step by step

  1. P(X < 60) = normalcdf(−∞, 60, 50, 8).
  2. P(X > 60) is the complement.

Final answer

P(X < 60) ≈ 0.894; P(X > 60) ≈ 0.106.

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IB-style question — find σ from the IQR

A normally distributed variable has interquartile range 13.49.

Find its standard deviation σ.

Step by step

  1. The quartiles sit 0.6745 standard deviations either side of the mean (invNorm(0.75) = 0.6745), so the IQR spans 2 × 0.6745 = 1.349 standard deviations.
  2. Solve for σ.

Final answer

σ = 10.

Q1 and Q3 lie 0.6745σ either side of the mean, so the IQR = 1.349σ — divide the IQR by 1.349 to recover σ.

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IB-style question — conditional on a normal region

X ~ N(20, 4²). Find P(X > 24 | X > 18).

Step by step

  1. Conditional: keep only X > 18, take the X > 24 slice.
  2. Each probability from normalcdf on the GDC.

Final answer

≈ 0.230.

IB-style question — find μ and σ from two probabilities

X ~ N(μ, σ²), with P(X < 50) = 0.2 and P(X < 70) = 0.9.

Find μ and σ.

Step by step

  1. Standardise each probability using invNorm to get the z-values, then write two equations.
  2. Subtract to eliminate μ.
  3. Back-substitute for μ.

Final answer

μ ≈ 57.9, σ ≈ 9.42.

Two given probabilities give two z-equations; subtracting eliminates μ to find σ, then back-substitute for μ.

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Standard areas you can use by hand: Without a calculator, use symmetry (P(X < μ) = 0.5) and the empirical rule: about 68% of data lies within 1σ of the mean, 95% within 2σ, and 99.7% within 3σ.

IB-style question — empirical rule

Heights are X ~ N(170, 10²) cm.

Use the empirical rule to estimate P(160 < X < 180).

Step by step

  1. 160 and 180 are μ − σ and μ + σ.
  2. Within 1σ → empirical rule.

Final answer

About 0.68 (68%).

Split the leftover symmetrically: Outside 1σ is 1 − 0.68 = 0.32, split into two equal tails of 0.16 each — handy for P(X > μ + σ).
Probability × how many: To find an expected number meeting a condition, find the probability with normalcdf, then multiply by the total number — exactly like n × P.

IB-style question — how many

Bolt lengths are X ~ N(50, 2²) mm.

A bolt is rejected if it is longer than 53 mm.

In a batch of 400 bolts, find the expected number rejected.

Step by step

  1. Probability one bolt is too long.
  2. Expected number = probability × 400.

Final answer

About 27 bolts are expected to be rejected.

Two steps, both shown: Show the probability and the × total — each usually earns a mark.

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X ~ N(20, 4²). Find P(X > 26). [2 marks]

Related Math AA HL Topics

Continue learning with these related topics from the same unit:

4.1.1Populations & samples
4.1.2Sampling techniques
4.10.1Prediction
4.11.1Conditional probability
View all Math AA HL topics

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