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Discover why IB Maths AI exams favour cumulative frequency graphs over raw tables and what this reveals about examiner priorities.

Learn why time management is more difficult in IB Maths AI exams and how interpretation-heavy questions change pacing.

Learn why IB Maths AI rewards reasoning over speed and how strong thinking leads to higher exam scores.

Understand why discrete random variables feel abstract in IB Maths AI and how to make sense of them for exam success.

Learn why IB Maths AI prioritises interpretation over calculation in discrete random variable questions and how to score consistently.

Understand why independence is central to IB Maths AI probability questions and how incorrect assumptions cost marks.

Learn why IB Maths AI multi-part questions test depth of understanding rather than stamina and how to approach them efficiently.

Low standard deviation isn’t always better in IB Statistics. Learn why context matters, common mistakes, and exam tips.

Box plots and histograms can show different patterns in IB Statistics. Learn why both matter and how to interpret them.

Grouped data loses detail in IB Statistics. Learn why this happens, common mistakes, and how examiners assess it.

Learn why percentiles are central to IB Maths AI statistics questions and how misunderstanding them leads to lost interpretation marks.

Learn why IB Maths AI awards more marks for explanation than final answers and how to maximise interpretation marks.

Learn why cumulative frequency graphs conceal distribution shape in IB Maths AI and how this affects interpretation and exam answers.

Learn why “reasonable answer” marks are crucial in IB Maths AI and how they reward thinking over perfect precision.

Understand why estimating the mean from cumulative frequency graphs is unreliable in IB Maths AI and how examiners expect you to handle it.

Learn why true random sampling is difficult in IB Maths AI contexts and how to explain these limitations for exam marks.

Learn why IB Maths AI students underestimate interpretation demands and how this misunderstanding leads to lost marks.

Learn why real-world data is rarely perfectly normal in IB Maths AI and how examiners expect you to discuss this.

Understand why extrapolation is risky in IB Maths AI regression questions and how examiners expect you to evaluate predictions.

Learn why IB Maths AI rewards explanation more than perfect numbers and how this affects marking and exam strategy.

Learn why IB Maths AI students confuse “and” vs “or” in probability questions and how to interpret exam wording correctly.