IA idea · Environment & climate
Are Atlantic hurricanes becoming more frequent?
Research question
Does the annual number of Atlantic hurricanes since 1966 follow a Poisson distribution, and is there a significant difference in the mean number per year between 1966–1995 and 1996–2025?
Make it yours, then agree it with your teacher.
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Why it makes a good exploration
Hurricane counts are small integers each year — ideal for the Poisson distribution. Testing for change, while recognising that satellites improved detection, is a thoughtful statistics IA with a real scientific debate behind it.
The mathematics you'll need
- Poisson distribution and goodness-of-fit
- Comparing means of two periods
- Mean–variance comparison
- Discussing detection bias
The statistics, step by step
Worked with every number shown, with what examiners look for and the common mistakes: Chi-squared goodness of fit · Binomial and Poisson models · Sampling and collecting data. Then run the same steps on your own data in Analyse my data, or start from the statistics workflow.
Where the data comes from
Count hurricanes per year from NOAA's HURDAT2 database.
- NOAA National Hurricane Center — HURDAT2 — Six-hourly track, wind and pressure for every Atlantic tropical cyclone since 1851.
Real data for this idea
- Primary source: NOAA National Hurricane Center (HURDAT2): HURDAT2 best-track data. Count storms per season in the Atlantic HURDAT2 file; satellite coverage began in the 1960s, so earlier counts are low. Licence: US government data; cite the dataset.
Links checked October 2026; we link to the data and never copy it. More free data sets.
A possible outline
- Define what you count (hurricane strength at any point).
- Justify the start year (satellite era).
- Test the Poisson fit.
- Compare periods.
- Reflect on detection, natural cycles and intensity vs frequency.
Pitfalls that cost marks
- Using pre-satellite years without discussing detection.
- Counting storms instead of hurricanes inconsistently.
- Over-interpreting a non-significant result.
Showing personal engagement
- Choose a season you remember from the news.
- Compare major hurricanes only.
- Explain the debate about hurricane trends in your own words.
See Criterion C: personal engagement for what examiners look for.
Which course is it for?
| Course | Fit | Maths to lean on |
|---|---|---|
| AA SL | Not a natural fit | The core technique sits in the AI course or at HL; an AA SL student could use it only as clearly explained new mathematics. |
| AA HL | Not a natural fit | The mathematics is mainly from the AI course; at AA HL the exploration would need an AA-level approach (calculus, proof or probability theory) to reach the top of Criterion E. |
| AI SL | Fits — ambitious at SL | Poisson distribution and goodness-of-fit; Comparing means of two periods |
| AI HL | Good fit | Poisson distribution and goodness-of-fit; Comparing means of two periods |
Level: Ambitious. Suits confident students; expect to learn some mathematics on your own. See how the IA differs between AA and AI, SL and HL.
How this idea reaches the top bands
Reflection (D)
For this idea, start with the weak points: using pre-satellite years without discussing detection; and counting storms instead of hurricanes inconsistently. Say how each one affects your answer.
Use of mathematics (E)
SL: poisson distribution and goodness-of-fit; comparing means of two periods; mean–variance comparison; discussing detection bias, each explained in your own words and carried out correctly.
How environment explorations reach the top bands in general: Environment & climate IA ideas. Guides: A · B · C · D · E · self-grade sheet.
Taking it further
Test whether intensity (maximum wind speed) has changed, not just frequency.
Extending it for HL
Add an HL technique the question genuinely needs: what an HL environment exploration adds.
See a complete IA, marked
When is the sea warm enough for our swimming club? A sinusoidal model of sea temperature (AI SL) is a complete environment exploration, marked on every criterion.
Frequently asked questions
Which IB Maths course is this IA idea for?
It works for AI SL and AI HL. We rate it Ambitious: it suits confident students, who should expect to learn some mathematics on their own.
What mathematics does this IA use?
Poisson distribution and goodness-of-fit, comparing means of two periods, mean–variance comparison and discussing detection bias.
Where can I get data for this IA?
Count hurricanes per year from NOAA's HURDAT2 database. Checked sources and tools: NOAA National Hurricane Center (HURDAT2) and NOAA National Hurricane Center — HURDAT2.
Turn this idea into your IA
The planner opens with “Are Atlantic hurricanes becoming more frequent?” filled in: the question, the maths and the data sources.
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