This module will address topics of:

Theory & Knowledge Exchange
Frequency tables and polygons, bar and pie-charts, scatter diagrams, mean, median, mode, range, standard deviation, histograms, skewness, cumulative frequency tables and graphs, boxplots and percentiles.

Fractional, decimal and percentage probability, relative frequency, Venn diagrams, sample space diagrams, addition and multiplication laws, independent events, conditional probability (Baye’s Theorem), probability trees, and standard probability notation.

Lines of regression, correlation coefficients, discrete random variables, probability distributions (normal, binomial and Poisson), central limit theorem, and hypothesis testing.

Proposition of a hypothesis, justification of a hypothesis, testing of a hypothesis, analysis of results, presentation of conclusions and critical evaluation of methods and reliability.

Practical Content
The above topics will be examined practically in tutorial classes.

CLASS-TEST: The class-test will test students on the maths content taught on the module. The nature of the test will be to explore all aspects of taught maths to gauge the student’s performance of using these concepts in practical case study settings (Learning Outcomes 1 to 2).


WRITTEN: At the end of the module students are required to write a brief reflection summarising what they have learned, how they have used this practically, and how they may use it in a future career (Learning Outcomes 3 and 4).

All teaching sessions will blend theory and practical learning. Students will be introduced to curriculum concepts and ideas and will then be able to apply theory to practical examples within the same sessions. In addition, students will be provided with a range of resources for independent study such as case studies, academic papers and industry stories. There will be a mixture of practical and theoretical formative (mock or practice) exercises which will help students build knowledge and confidence in preparation for summative (formal) assessment.

1. Understand and use standard descriptive statistical, and probability techniques.

Knowledge and Understanding, Enquiry

2. Communicate and explain in detail complex statistical concepts and techniques to others.

Application, Enquiry

3. Reflect on personal learning and how this can be employed in a chosen career path.

Reflection

4. Identify further learning topics and concepts related to subject discipline.

Enquiry

Standard PC

All texts and electronic resources will be updated and refreshed on an annual basis and available for students via the online Study Links resource platform. All reference materials will be collated and curated and aligned to Equality, Diversity & Inclusion indicators.

Core Text/Resource:
Mittal, P, K, (2018), Mathematics for Degree Students (For B.Sc. First Year), S Chand, ASIN: B06XK8MXGS
Mendenhall, W, Beaver, R, J and Beaver, B, M, (2019), Cengage Learning; 15th ed. Edition, ISBN-10: 1337554421
Harford, T, (2021), How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers, The Bridge Street Press, ISBN-10: 0349143862
All resources will be updated regularly and available via a module KeyLinks online function.

All teaching sessions will blend theory and practical learning. Students will be introduced to curriculum concepts and ideas and will then be able to apply theory to practical examples within the same sessions. In addition, students will be provided with a range of resources for independent study such as case studies, academic papers and industry stories. There will be a mixture of practical and theoretical formative (mock or practice) exercises which will help students build knowledge and confidence in preparation for summative (formal) assessment.