A Level Statistics Topics by Exam Board: Full List

A Level Statistics – currently only offered by Pearson Edexcel (opens in a new tab) – consists of 21 topics across three areas: data and probability, statistical inference, and statistics in practice.

To help you plan your revision, we’ve pulled together all A Level Statistics topics into one place. Don’t worry about wading through the 52 pages of the specification; our guide is designed to give you a practical overview of what you’ll actually be tested on, helping you to take your A Level Statistics exams with clarity and confidence.

Key Takeaways

• Pearson Edexcel A Level Statistics consists of 21 topics

• The 21 A Level Statistics topics are assessed across three areas: data and probability, statistical inference, and statistics in practice

• Use this guide as a shortcut for the A Level Statistics specification and as a revision checklist

Why It’s Important to Know Your Exam Board

Although subject content often overlaps across exam boards, each exam board has a different syllabus. The same subject can therefore be taught very differently in one exam board compared to another, with varying topics, skills and assessment methods.

Knowing exactly which topics your exam board covers means you can create a focused revision plan. You won't waste time studying content that won't be tested, and you'll know exactly what to expect when it comes to exams.

Pearson Edexcel is currently the only exam board offering A Level Statistics. If you’re taking A Level Statistics, your exam board is Pearson Edexcel.

Pearson Edexcel A Level Statistics Topics (9ST0)

The core subtopics in each of the 21 A Level Statistics topics are listed below:

1. Numerical measures, graphs and diagrams

• Statistical diagrams, e.g. bar charts and stem and leaf diagrams

• Appropriate data representation and misrepresentation

• Outliers

2. Probability

• Language and symbols associated with set theory

• Tree diagrams, Venn diagrams and two-way tables

• Calculations, comparisons and probability laws

3. Population and samples

• Simple and unrestricted random samples

• Advantages and limitations of sampling techniques and methods 

• Practical constraints of collecting unbiased data

4. Introduction to probability distributions

• Terms for variability

• Probability calculations

• Discrete random variables

• Graphical representations

5. Binomial distribution

• Appropriate binomial models

• Probability formulas and tables

• The mean and variance

6. Normal distribution

• Properties of normal distribution

• Probabilities and unknown parameters

• Cases in which normal distribution is used to approximate binomial distribution

7. Correlation and linear regression

• Spearman’s rank correlation coefficient or Pearson’s product moment correlation coefficient

• Tables to test for significance of a correlation coefficient

• Appropriate conditions for methods of calculating correlation

• Least squares regression line

8. Introduction to hypothesis testing

• Parameter, statistic, unbiased and standard error

• The language of statistical hypothesis testing, e.g. null or alternative hypothesis

• Appropriate sampling

• Tests for the proportion in the binomial distribution and for the mean of a normal distribution

9. Contingency tables

• Tables from real data

• Use of a χ² test

• Expected frequencies

10. One and two sample non-parametric tests

• Sign or Wilcoxon signed-rank tests

• Wilcoxon rank-sum test

11. Bayes’ theorem

• Conditional probabilities

• Tree diagrams

12. Probability distributions

• Binomial, normal, Poisson and exponential distributions

• The mean and variance of linear combinations of independent random variables

• Probabilities for linear combinations of two or more independent normal distributions

13. Experimental design

• Issues, e.g. experimental error and randomisation

• Paired comparisons

• Completely random and randomised block designs

14. Sampling, estimates and resampling

• Parameter, statistic, unbiased and standard error

• Central limit theorem

15. Hypothesis testing, significance testing, confidence intervals and power

• Strength of conclusions and Type I and Type II errors in hypothesis tests

• The effect of a change in sample size

• Confidence intervals for the mean

• Critical regions or 𝑝-values

16. Hypothesis testing for 1 and 2 samples

• Difference

  • of two means for two independent normal distributions

  • between two binomial proportions

• Interpreting test results

17. Paired tests

• Sign, Wilcoxon signed-rank or paired 𝑡-test

• Appropriate test selection

• Interpretation of results in context

18.  Exponential and Poisson distributions

• Poisson model

• Exponential distribution

• Evaluation of probabilities for Poisson and exponential distributions

19. Goodness of fit

• Statistical goodness of fit tests for

  • binomial, Poisson, normal and exponential distributions 

  • a specified discrete distribution

20. Analysis of variance

• One and two-way

• Identification of assumptions and interpretations in context

21. Effect size

• The notion of effect size as a complementary methodology to standard significance testing

• Cohen’s 𝑑

In addition to the 21 topics, you’ll also cover the five stages of the Statistical Enquiry Cycle (SEC):

1. Initial planning

2. Data collection

3. Data processing and presentation

4. Interpretation of results

5. Evaluation and review

The table below outlines which topics you could be tested on in each of the three A Level Statistics exam papers:

How to Use Topic Lists for Revision

Create a revision plan

Print or copy out the A Level Statistics topics into a checklist. Use the traffic light system (opens in a new tab) to prioritise the topics you feel least confident in, and tick each topic off as you revise. Seeing progress is really motivating, and it stops you from accidentally skipping topics.

Practise with past papers

Once you’ve revised the relevant topics, test your knowledge and understanding by completing A Level Statistics past papers. Use the table above to remind you of which topics could come up in each paper, and assess how you did against the relevant mark scheme.

Frequently Asked Questions

Do I need to revise all A Level Statistics topics for the exam?

Ultimately, yes. Paper 3 could test you on any of the 21 topics, and Paper 1 and Paper 2 each still require knowledge of around half of the topics.

Use a checklist to make your revision more manageable, and use our table above to remind yourself of what each paper assesses to help create a relevant revision plan.

Are these topics the same across all exam boards?

Pearson Edexcel is currently the only exam board offering A Level Statistics, which consists of 21 topics.

How do I know which topics I struggle with most?

Alongside the traffic light system, look at which topics you tend to get the lowest marks on in mock exams or past paper questions. Prioritise revising the areas you’re least confident in.

Do all topics come up in every exam paper?

No. Paper 3 is the only paper that could test you on all 21 topics; Paper 1 could test you on topics 1–7, 11–13 and 18, and Paper 2 on topics 7–10, 13–17 and 19–21.

All three exam papers test you on the SEC.

Final Thoughts

With our full list of Pearson Edexcel A Level Statistics topics, you’ll now have a clear idea of exactly what you’ll be tested on, and in which paper. Rather than relying on a lengthy specification, you can now quickly and easily create a revision checklist tailored to each of your three A Level Statistics exams.

Though revising 21 topics might seem overwhelming, keep in mind that many overlap: topics 8, 15 and 16, for instance, all cover hypothesis testing. This means that once you’ve revised one topic, other related topics will be easier to grasp. 

Gradually build up your confidence in A Level Statistics by focusing on the topics you find trickiest first.

Good luck!