Summary OCR MEI AS Level Mathematics Notes (Part 2)
Boost your MEI OCR A Level Mathematics Year 1 (AS) grade with these clear, concise handwritten revision notes; Part 2 of 2, covering the remaining pure, statistics, and mechanics foundations. Created by a Cambridge University Economics graduate who achieved A* in Mathematics and Further Mathematics using these very notes, this pack is designed to help you understand concepts quickly and apply them accurately in exams. Modules covered in this pack: 11. Integration 12. Vectors 13. Exponentials and Logarithms 14. Data Collection 15. Data Processing, Presentation and Interpretation 16. Probability 17. Binomial Distribution 18. Hypothesis Testing 19. Kinematics 20. Forces and Newton’s Laws 21. Variable Acceleration Inside you’ll find: - The key content from the MEI OCR A Level Mathematics Year 1 (AS) textbook, distilled for efficient revision - Clear, step-by-step explanations using exam-appropriate methods - Worked examples aligned with mark scheme expectations - Common pitfalls highlighted to help you avoid unnecessary errors - A clean, logical layout ideal for both learning and last-minute revision Perfect for: - Students targeting A or A* grades - Those who find the textbook dense or overwhelming - Structured revision before mocks or final exams Save hours of note-making and revision planning. These notes turn challenging mathematical topics into clear, exam-ready summaries so you can revise with confidence and focus on completing practice questions to score highly.
Connected book
Written for
- Study Level
-
A/AS Level
- Examinator
-
OCR
- Subject
-
OCR MEI AS Level Mathematics
- Unit
-
Module 11-21 (H630)
Document information
- Summarized whole book?
- No
- Which chapters are summarized?
- Chapter 11 to 21
- Uploaded on
- December 14, 2025
- Number of pages
- 82
- Written in
- 2022/2023
- Type
- Summary
Subjects
- mei ocr
- maths
- mei notes maths
- as level maths notes
- pure maths
- statistics
- mechanics notes
-
integration
-
vectors
-
exponentials
-
logarithms
-
data collection
-
data processing
-
probability
-
bionomial distribution
Also available in package deal