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Math Analysis & Approaches unit guide

Statistics and probability

Correlation and regression, probability, discrete and continuous random variables, binomial and normal distributions.

Statistics is the most GDC-dependent unit in AA and the one where Paper 2 marks are won or lost on calculator fluency rather than understanding. The distributions are all menu operations; what gets examined is whether you can tell which distribution a worded problem describes, and whether you set up the inequality the right way round. Students who practise reading questions rather than running calculations tend to find this the highest-scoring unit in the course.

Topics in this unit

Statistics ToolkitCorrelation & RegressionProbabilityDiscrete Random VariablesBinomial DistributionNormal DistributionContinuous Random Variables

What gets examined

  • Choosing between binomial and normal from the description - fixed trials and two outcomes, or a continuous measurement.
  • Normal distribution problems in both directions, including inverse normal to find a boundary value from a probability.
  • Binomial probabilities for exactly, at most and at least, and translating each into calculator input.
  • Expected value and variance for a discrete random variable from a probability distribution table.
  • Correlation coefficient and regression line from data, and what r does and does not tell you.
  • Conditional probability and independence, usually via a tree diagram or a Venn diagram.

How to revise it

Decide the distribution before touching the calculator

Counting successes in a fixed number of trials is binomial. A continuous measurement clustered around a mean is normal. Nearly every error here is the right method on the wrong distribution.

Rewrite "at least" as one minus "at most"

P(X >= 3) = 1 - P(X <= 2). Doing this conversion on paper before reaching for the GDC prevents the off-by-one that this topic is notorious for.

Know your inverse normal

Given a probability, find the value. It is a distinct menu operation from the forward direction and it appears every session. Practise until it is automatic.

Say what correlation does not mean

A strong r does not imply causation, and questions ask about this directly. One sentence, reliably available.

Where marks get lost

  • Using P(X < 3) where P(X <= 3) was meant, which matters for a discrete variable and not for a continuous one.
  • Extrapolating a regression line beyond the data and treating the result as reliable.
  • Forgetting that probabilities in a distribution table must sum to one when solving for an unknown.
  • Confusing the standard deviation with the variance in a normal calculation.
  • Treating dependent events as independent in a tree diagram - the second branch changes.

Practise this unit

Reading about a unit only goes so far. Work through real IB-style questions on it, with mark schemes.