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v0.1.894
NotesMath AI HLTopic 4.9Normal Probabilities
Back to Math AI HL Topics
4.9.21 min read

Normal Probabilities

IB Mathematics: Applications and Interpretation • Unit 4

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Contents

  • Normal probabilities from context
  • How to calculate P(X < a), P(X > a), P(a < X < b)
  • Inverse normal (finding cut-off values)
  • Exam traps and past-paper habits

Normal probabilities from context

Big idea: For a normal variable, a probability is an area under the bell curve.

P(X < a) is the area to the left of a.

[Diagram: math-normal-curve] - Available in full study mode

Example: if test scores are normal, P(score < 70) is the proportion of students scoring below 70.

AI SL method — use the GDC: Always write X ~ N(μ, σ²), then use your GDC: normalcdf(lower, upper, μ, σ).

There are no z-scores or z-tables in AI SL — you enter μ and σ straight into the calculator.

How to calculate common normal probabilities

Worked example

Let X~N(100,152).

Find P(X<120).

Step by step

  1. Write formula first: z=(x-mean)/sd
  2. Use table/calculator to get P(Z<1.33)
  3. P(Z<1.33)≈0.908

Final answer

P(X<120)≈0.908.

TargetCalculator setup
P(X<a)normalcdf(-1E99,a,mean,sd)
P(X>a)normalcdf(a,1E99,mean,sd)
P(a<X<b)normalcdf(a,b,mean,sd)

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Inverse normal: finding cut-off values

When inverse is needed: If the probability is given and x is unknown, use inverse normal.

Worked example

Heights are X~N(170, 62).

Find the height exceeded by top 10%.

Step by step

  1. Top 10% means left area = 0.90
  2. Use invNorm(0.90,170,6)
  3. x≈177.7 cm

Final answer

Top 10% cut-off is about 177.7 cm.

Exam wording: "Exceeded by top 10%" means use cumulative 0.90, not 0.10.

Exam traps and past-paper habits

Common mistakes

  • Confusing the upper tail with the lower tail.
  • For invNorm, entering the tail area instead of the cumulative (left) area.
  • Rounding too early in the working.

Safe method

  • Sketch the curve and shade the required region first.
  • For ''top p%'', use cumulative area 1 − p in invNorm.
  • Keep full accuracy and round only the final answer to 3 s.f.

Exam Tips:

  • Write X ~ N(μ, σ²) first.
  • Mark the required tail with a quick sketch.
  • State the final probability to 3 s.f. unless told otherwise.

IB Exam Questions on Normal Probabilities

Practice with IB-style questions filtered to Topic 4.9.2. Get instant AI feedback on every answer.

Practice Topic 4.9.2 QuestionsBrowse All Math AI HL Topics

How Normal Probabilities Appears in IB Exams

Examiners use specific command terms when asking about this topic. Here's what to expect:

Define

Give the precise meaning of key terms related to Normal Probabilities.

AO1
Describe

Give a detailed account of processes or features in Normal Probabilities.

AO2
Explain

Give reasons WHY — cause and effect within Normal Probabilities.

AO3
Evaluate

Weigh strengths AND limitations of approaches in Normal Probabilities.

AO3
Discuss

Present arguments FOR and AGAINST with a balanced conclusion.

AO3

See the full IB Command Terms guide →

Related Math AI HL Topics

Continue learning with these related topics from the same unit:

4.1.1Population and Samples
4.1.2Data Classification
4.1.3Sampling Techniques
4.1.4Data Reliability and Outliers
View all Math AI HL topics

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Command terms, paper structure, and mark-scheme tips for Math AI HL

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4.9.1Normal Distribution Properties
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