MA142-10 Calculus 1
Introductory description
Mathematical Analysis is the heart of modern Mathematics. Calculus usually stands for Analysis, focused on calculations rather than proving theorems. This module is the first in a series of modules where the subject of Anaysis is developed with a focus on calculations.
Module aims
The principal aim is to develop Analysis in dimension 1, with much greater precision and rigour than the students had at school. While the high-school Analysis is focusing on problem solving methods, the university-level Analysis is switching the focus to the mathematical concepts and clarity of thought.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
- Real numbers
- Limits
- Series
- Continuity
- Uniform continuity
Learning outcomes
By the end of the module, students should be able to:
- develop deep understanding of the real numbers and the symbol `infinity'
- develop working knowledge of sequences and series, including limits, conditional and absolute convergence
- learn the properties of continuous and absolutely continuous functions
Indicative reading list
M. Hart, Guide to Analysis, Macmillan.
M. Spivak, Calculus, Benjamin. R.G Bartle and D.R Sherbert, Introduction to Real Analysis (4th Edition), Wiley (2011)
L. Alcock, How to think about Analysis, Oxford University Press (2014)
View reading list on Talis Aspire
Subject specific skills
Calculus gives first-year undergraduates a first excursion in to pure mathematics. The students will gain a new perspective and a deeper understanding of familiar mathematics which they have seen in school (e.g. real numbers, functions and differentiation). In Calculus, these concepts are developed with mathematical rigour, which characterises much of university mathematics to follow.
Transferable skills
Students will acquire key reasoning and problem solving skills, empower them to address new problems with confidence.
Study time
| Type | Required |
|---|---|
| Lectures | 20 sessions of 1 hour (20%) |
| Online learning (independent) | 9 sessions of 1 hour (9%) |
| Placement | 13 hours (13%) |
| Assessment | 58 hours (58%) |
| Total | 100 hours |
Private study description
No private study requirements defined for this module.
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Assessment group D
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| Assignments | 15% | 20 hours | No |
| In-person Examination | 85% | 38 hours | No |
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Assessment group R
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| In-person Examination - Resit | 100% | No | |
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Feedback on assessment
Marked homework (both assessed and formative) is returned and discussed in smaller classes. Exam feedback is given.
Courses
This module is Core for:
- Year 1 of USTA-G302 Undergraduate Data Science
- Year 1 of USTA-G304 Undergraduate Data Science (MSci)
- Year 1 of UCSA-G4G1 Undergraduate Discrete Mathematics
- Year 1 of UCSA-G4G3 Undergraduate Discrete Mathematics
- Year 1 of USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
- Year 1 of USTA-Y602 Undergraduate Mathematics,Operational Research,Statistics and Economics