OCR A Level Further Mathematics A Statistics Paper 1 2025 Qp

Get the official OCR A Level Further Mathematics A Y542/01 Statistics question paper from the June 2025 exam series. This examiner-authentic PDF contains the complete set of OCR assessment questions covering probability distributions, hypothesis testing, regression, correlation, statistical modelling and continuous probability exactly as candidates received them in the live examination.

This OCR Y542/01 June 2025 question paper includes questions on linear regression estimates for bivariate data, Poisson-distribution modelling of tree populations, Central Limit Theorem applications, normal-distribution hypothesis testing and combined normal random variables. The paper also explores advanced statistical methods including Wilcoxon signed-rank testing, chi-squared tests for association, Spearman’s rank correlation coefficient, probability-density functions, percentiles and distribution identification using sample statistics and observed frequencies. Designed to test rigorous statistical reasoning, modelling assumptions and analytical interpretation under timed conditions, this paper is ideal for OCR Further Mathematics revision and exam preparation. Pair it with the matching OCR Y542/01 June 2025 mark scheme on markscheme.net for complete examiner-standard revision and worked-solution practice. Updated for the 2025/2026 academic year, mobile-friendly and instantly downloadable from markscheme.net.

This document is designed for Year 13 OCR A Level Further Mathematics students preparing for the 2026 examination series, including independent learners, resit candidates and high-achieving mathematics students seeking authentic OCR exam practice in Further Statistics.

Teachers, tutors, sixth-form mathematics departments and revision-course providers can use this OCR Y542/01 paper for timed mock examinations, hypothesis-testing workshops, probability-modelling lessons, statistical-reasoning seminars and data-analysis practice. It is especially valuable for students aiming to strengthen distribution modelling, interpretation of statistical evidence and high-level analytical problem-solving under real exam conditions.