BUSINESS MATHEMATICS - 2023/4
Module code: MAN1060
The module teaches tools and techniques of Business Mathematics.
Surrey Business School
HAN Liang (SII DUFE)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 4
JACs code: G100
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 117
Lecture Hours: 22
Seminar Hours: 11
Prerequisites / Co-requisites
Indicative content includes:
Basic numeracy, Sampling techniques, Data collection and Presentation, Descriptive Statistics, Index Numbers, Probability, Probability Distributions, Inference and Hypothesis Testing, Correlation, Linear and Multiple Regression, Time series, Forecasting, Linear Programming techniques and Financial Mathematics.
|Assessment type||Unit of assessment||Weighting|
|School-timetabled exam/test||CLASS TEST SET DATE AND TIME||30|
|Examination||EXAM SET TIME AND DATE||70|
There are two summative assessments for this module: a class test and an end of semester examination.
The class test will comprise multiple choice questions and/or questions requiring short written answers.
The exam paper will include scenario questions. Questions may contain several parts (part (a), part (b) etc).
Assessments will include both quantitative and qualitative questions.
Quantitative questions are designed to assess numerical, application of knowledge and analytical skills.
Qualitative questions will assess application of knowledge, synthesis, creative thinking and problem-solving skills.
Formative assessment and feedback
Formative assessments such as a sample class test and exam paper will be available to support students in preparation for summative assessments and to provide ongoing feedback. Such feedback will help students identify their strengths and weaknesses and help develop revision plans for the summative assessments.
Students are also expected to engage with other feedback provided during seminars and feedback and advice hours throughout the semester.
- Apply mathematical tools required in future modules within the undergraduate degree programme.
|001||Identify and use appropriate basic mathematical tools including index numbers||KCPT|
|002||Analyse and present data||KCPT|
|003||Use probability techniques, apply probability distribution theory, make inferences and test hypotheses.||KCT|
|004||Calculate correlations and demonstrate tools for forecasting, including linear, multiple regression and time series||KCPT|
|005||Use statistical methods of linear programming.||KCPT|
|006||Apply financial mathematics techniques||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is based on a hybrid teaching model, incorporating elements of both live and on-demand learning.
On-demand learning is designed for students to explore the topics in their own time and includes a range of guided learning activities. Guided learning activities may include pre-recorded videos, practice questions & solutions, quizzes, discussion forum and links to further reading.
Live learning allows students to explore and engage in discussions on the topics and also practise more complex questions and receive answers and feedback to queries from their tutor.
This learning and teaching strategy provides students with the opportunity to acquire knowledge and to understand the relevant theory and develop effective solutions for decision making in the context of case study scenarios.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: MAN1060
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.