Updated 12 October 2026 · By Pete Bromfield, former Head of Maths with IB examining experience

IA idea · Statistics & hypothesis testing

Are our summers getting wetter or drier?

AI SLAI HLAA SL Accessible Also in: Environment

Research question

Is mean summer rainfall at [a UK weather station] significantly different in 1991–2020 compared with 1961–1990?

Make it yours, then agree it with your teacher.

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Why it makes a good exploration

Climate normals are 30-year averages, and comparing two of them is exactly how meteorologists describe change. Met Office station records make this a clean, local two-sample test.

The mathematics you'll need

Descriptive statistics and box plots
Two-sample t-test and its assumptions (AI)
Linear regression of rainfall against year
Variability and standard deviation

Modelling the data, step by step

This idea usually needs a straight-line model. See it worked step by step, with a criterion tip at every step: Straight line y = mx + c.

Model your own data Paste it from Desmos, GeoGebra or a spreadsheet and get the same play-by-play with your numbers. New to modelling? Start with the modelling workflow. Writing it up? The IA modelling planner comments on each paragraph as you draft — it never writes it for you.

The statistics, step by step

Worked with every number shown, with what examiners look for and the common mistakes: t-test: two-sample and paired · Descriptive statistics and box plots. Then run the same steps on your own data in Analyse my data, or start from the statistics workflow.

Where the data comes from

Download monthly station data from the Met Office historic station pages and sum June–August each year.

Met Office historic station data — Monthly max/min temperature, rainfall, frost days and sunshine for 37 UK stations, some from 1853.

Real data for this idea

Primary source: Met Office historic station data: Historic station data. Choose the station nearest you; the table gives monthly maximum and minimum temperature, rainfall and sun hours. Licence: Check the terms on the Met Office page.

Links checked October 2026; we link to the data and never copy it. More free data sets.

A possible outline

Explain the station and the data (including provisional values).
Compute summer totals and describe both periods.
Run the t-test; check assumptions.
Look at the trend and at variability, not just the mean.
Reflect on station changes and natural variability.

Pitfalls that cost marks

Missing months treated as zero.
Ignoring that rainfall is often skewed.
Over-claiming about climate change from one station.

Showing personal engagement

Choose the station nearest your home.
Compare with temperature at the same station.
Relate to a local flood or drought you remember.

See Criterion C: personal engagement for what examiners look for.

Which course is it for?

Course	Fit	Maths to lean on
AA SL	Good fit	Descriptive statistics and box plots; Linear regression of rainfall against year
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	Good fit	Descriptive statistics and box plots; Two-sample t-test and its assumptions
AI HL	Fits, but add an HL technique	Descriptive statistics and box plots; Two-sample t-test and its assumptions

Level: Accessible. A good first extended piece of maths, with room to go deeper. 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: missing months treated as zero; and ignoring that rainfall is often skewed. Say how each one affects your answer.

Use of mathematics (E)

SL: descriptive statistics and box plots; two-sample t-test and its assumptions; linear regression of rainfall against year; variability and standard deviation, each explained in your own words and carried out correctly.

How statistics explorations reach the top bands in general: Statistics & hypothesis testing IA ideas. Guides: A · B · C · D · E · self-grade sheet.

Taking it further

Compare the variance of the two periods (are extremes more common?) or test several stations.

Extending it for HL

Add an HL technique the question genuinely needs: what an HL statistics exploration adds.

See a complete IA, marked

Should I lease or buy my first car? (AI SL) is a complete statistics exploration, marked on every criterion.

Frequently asked questions

Which IB Maths course is this IA idea for?

It works for AI SL, AI HL and AA SL. We rate it Accessible: a good first extended piece of maths, with room to go deeper.

What mathematics does this IA use?

Descriptive statistics and box plots, two-sample t-test and its assumptions (AI), linear regression of rainfall against year and variability and standard deviation.

Where can I get data for this IA?

Download monthly station data from the Met Office historic station pages and sum June–August each year. Checked sources and tools: Met Office historic station data.

Turn this idea into your IA

The planner opens with “Are our summers getting wetter or drier?” filled in: the question, the maths and the data sources.

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