Overview
The Kings Degree Pathway Programme is
one
of the most highly academic and successful
pathways to leading UK universities.
Data for Maths and Science is a compulsory module within the Programme, and is specifically designed to prepare students for the rigours of academic study at UK university.
Key Facts
- 6 January 2025
- April 2025 (Extended programme only)
- July 2025 (Extended programme only)
- September 2025
- Bournemouth
- Brighton
- London
- Oxford
- Academic: Completed 11-12 years of schooling
- English: IELTS 5.5 or equivalent
- 1 Academic Year (3 terms)
- Extended programme: 1-2 Academic Years (4-7 terms)
- Around 25 hours per week of taught classroom lessons plus tutorials, university counselling, super-curricular, extra-curricular and enrichment activities.
Learning outcomes
- The ability to structure, store and analyse numerical and non-numerical data.
- Knowledge of and competency in generic computer packages such as Excel
- The ability to represent data using a variety of graphical forms.
- The ability to understand numerical data using standard statistical methods.
- An appreciation of the application of statistics to modelling real-world situations.
- An understanding of notions of statistical testing.
- An understanding of the use of algorithms to solve real-world problems.
- A sophisticated understanding of data presented by others.
- An understanding of real-world applications involving forces and acceleration.
Course content and structure
The Degree Pathway Programme is highly flexible, and able to adapt to the needs and academic aspirations of each student. It does this through a combination of core
modules and a series of elective modules which can be combined in different ways to create main subject streams.
Data for Maths and Science is one of the compulsory modules offered, and an overview of the syllabus content is shown below.
Course structure and content
- Computer applications and statistics
- Computer security and good organisation practice
- Making backups of files and folders
- Using Microsoft Word to produce well presented academic reports
- Using Microsoft Excel to enter data, formulae and functions
- Using Microsoft Excel to represent, analyse, format and print data
- Measures of location and dispersion: mean, median, mode, range, quartiles, standard deviation, skewness
- Histograms, cumulative frequency diagrams, box and whisker plots, pie charts and stem and leaf diagrams
- Statistical analysis
- Sampling methods (random, systematic, stratified, quota, opportunity and cluster)
- Surveys and questionnaires (writing and analyzing)
- Probability, probability trees, Venn diagrams, conditional probability
- Critical reading of data presented by others
- Developing skills with Microsoft Excel (e.g. IF, VLOOKUP, CORREL, combo boxes, option buttons, spinners)
- Algorithms applied to graphs and networks
- Correlation of data
- Pearson’s Product Moment Correlation
- Coefficient and Spearman’s Rank Correlation
- Regression lines
- Significance testing
- Random variables
- Uniform and binomial distributions
- Expectation and variance
- Normal distribution
- Critical path analysis and GANTT diagrams
- Forces
- Moments
- Acceleration
- Vectors
Recommended reading
Below is a list of text books normally used on this course, as well as books which may help you prepare for your studies prior to arrival. In many cases the textbooks will be supplied by the school, and you may borrow them for the duration of your time at school.
- Edexcel AS and A level Mathematics Statistics and Mechanics Year 1 2017
- Edexcel AS and A level Mathematics Statistics and Mechanics Year 2 2017
- Pearson Edexcel Decision Mathematics 1 D1 published in 2009
Sample academic calendar (2023-2024)
Year 1
- 11th: term starts
- Student induction
- 23 – 27th: half term
- Progress tests
- University fairs and talks
- 15th: term ends
- End of term exams
- 15th – 16th: half term
- Progress tests
- University fairs
- End of term exams
- 22nd: term ends
