Mathematics and Statistics
Study Board of Business Economics
Teaching language: English
EKA: B100104X12, B100104X02, B100104412, B100104112, B100104402, B100104102
Censorship: Second examiner: None
Grading: 7-point grading scale
Offered in: Soenderborg, Odense
Offered in: Autumn
Level: Bachelor
Course ID: B100104X01, B100104401, B100104101
ECTS value: 10
Date of Approval: 20-03-2018
Duration: 2 semesters
Course ID
Course Title
Teaching language
ECTS value
Responsible study board
Date of Approval
Course Responsible
Offered in
Level
Offered in
Duration
Mandatory prerequisites
Recommended prerequisites
Aim and purpose
The objective of this course is to provide the student with mathematical and statistical for solving problems within the area of business administration. The objective is also to give the student an understanding of the interaction between mathematics, statistics and economic problems.
The course thus provides tools that are used in other subjects, for example Corporate Finance, Microeconomics, and Advanced Quantitative Analysis. This course provides the student with skills within functional analysis in particular, which is used e.g. investment theory, finance and macroeconomics. The course also provides a brief introduction to matrix algebra. Calculus is used to deduce and calculate elasticity of supply and demand, and to calculate profits and losses in trade, while optimization and equation systems are used in the planning of production and the planning of a company's marketing efforts. Matrix algebra is used to solve equation systems with multiple unknowns. Such systems are seen, for example, in statistical analyses and in models for economic planning. Finally, an introduction to integral theory is provided. Integral methodology is particularly used in Investment and Corporate Finance and Trade theory in order to find the gains from trade.
The course also gives the student skills in both fundamental techniques of data processing and presentation, and in concepts and methods to be used in analysis of data with a view to solving economic problems. The acquired skills can be used in several subsequent subjects. For example, they may form the basis for constructing hypotheses putting them to the test to compare the impact of e.g. advertising campaigns, surveys of the distribution of newspaper ads during a specific period, modelling of portfolios, surveys of the demand for tourist travels, etc. Emphasis is on giving the student an understanding of statistical methods in interaction with processing using statistical calculation software.
Content
The following topics are addressed in order to achieve the objectives of the course.
Topics in the autumn semester:
Functions of several variables
•Partial differentiation
•Implicit differentiation
Optimisation of functions that are relevant in economics
•Primary and secondary conditions for maxima and minima
•Use of the Lagrange method for optimization under constraints with economically motivated examples - including economic interpretation of Lagrange multipliers
•Geometric interpretation of functions of several variables - level curves, surfaces, etc.
Integration
•Calculation rules for integrals
•Rules for exponential and power functions
•Interpretation of integrals in relation to areas, including applications
Introduction to matrix algebra
Topics in the spring semester:
Descriptive statistics
•Selection of samples - simple random
•Central tendency, variation, skewness and extremes
Discrete and continuous distributions
•Including Binomial, Poisson and Normal distribution
•Variance-covariance of a set of stochastic variables, including linear combinations by means of matrix algebra.
Confidence intervals and hypothesis testing for
•Mean value and variance
Analysis of cross tables and goodness-of-fit tests
One-tailed variance analysis
Simple and multiple Methods in regression.
Learning goals
The student should be able:
•To apply calculus to functions of several variables and optimization for solving economic problems;
•To identify the correct method for solving a given problem;
•To assess whether the results obtained are correct;
•To relate statistical methods to frequently occurring problems in economics and business administration;
•To describe, analyse and interpret data using calculation software such as the “Analysis Tool Pack” in Excel or the add-in Megastat;
•To use statistical methods and analyses to investigate problems in economics and business economics, including - based on a concrete problem and a concrete data set
•To describe relevant parts of the data set
•On the basis of the description, to construct hypotheses on relationships
•To select and use relevant methods to examine the validity of the hypotheses
•To give a relevant interpretation of the analyses conducted
•To discuss the assumptions and limitations of the selected statistical analysis methods and also to assess the applicability of the selected models to the issue in question.
Literature
Reading list for the autumn semester:
Ian Jacques, Mathematics for Economics and Business. Pearson Education, latest edition.
Supplementary notes.
Reading list for the spring semester:
Bowerman, O'Connell, Orries & Porter "Essentials of Business Statistics", McGraw-Hill, latest edition.
Supplementary readings: Erik M. Bøye, "Statistics Companion", Guide for use of textbooks in Statistics, Swismark.
Teaching Method
IT is used as an integral part of the teaching, based on both the “Analysis Tool Pack” add-in in the Excel spreadsheet. Subsidiary the add-in Megastat can be used.
The students acquire knowledge of the subject area through independent literature studies supported by lecture sessions aiming to provide an overview of the area and links between different parts of the subject. The lectures are also used to enhance the textbook explanations of particularly difficult topics.
The students develop skills in applying the scientific methods used in the field by working with assignments in the subject. This process is facilitated by exercise sessions enabling students to debate issues when solving assigned problems and get feedback on their own work.
Workload
In the autumn: 2 lectures and 1 exercise session per week for 15 weeks. The exercises may be given as 2 exercise sessions every second week.
In the spring: 2 lectures and 2 exercise sessions per week for 15 weeks.
Students will be required to do 250 hours of work, which is expected to be spent as follows:
•Lectures: 60 hours
•Exercise sessions: 45 hours
•Preparations for exercise sessions and lectures 90 hours
•Preparations for examination: 30 hours
•Written examination (first part-examination): 3 hours
•Take home assignment (second part-examination): 22 hours.
Examination regulations
Exam - 1st semester
Name
Exam - 1st semester
Timing
Exam: January.
Reexam: February.
Exam on the autumn topics.
Examination form at the re-exam can be changed.
Rules
-3 is not allowed
Tests
Exam
Name
Exam
Form of examination
Written examination on premises
Censorship
Second examiner: None
Grading
7-point grading scale
Identification
Student Identification Card - Exam number
Language
English
Duration
3 hours written exam.
Length
No limit.
Examination aids
No digital aids allowed. It is only allowed to work in the retrieved Word-template. It is not allowed to use other templates, mathematical templates or other PC-based programs. See also under special circumstances. It is allowed to bring along books, notes, and pocket calculator. Maximum allowed pocket calculator is Texas TI-89 / TI-nspire. The pocket calculator must not be connected to the computer. A list of allowed pocket calculators is available from the Blackboard page of the course. It is not allowed to use the build-in pocket calculator in the computer. It is not allowed to bring IPads/tablets/smartphones. It is not allowed to communicate with others.
Assignment handover
Will be handed out in the examination room.
Assignment handin
Only digital submission, via SDUassignment in the course page in Blackboard.
ECTS value
5
Additional information
The examination is held using the students own PC with wireless network access to the university.
The Internet must only be used to access SDUassignments in order to submit and retrieve the Word-template to be used for the exam. Aside from this activity the Internet must be used during the examination.
Preparation: The assignment has to be written in a Word-template that is handed out via SDUassignment at the beginning of the exam. Graphs, formulas and similar may be written by hand and transferred to the template by use of either a digital pen or a hand scanner. See under special circumstances.
Special Circumstances:
If you have bought the book by Ian Jacques for the course as an e-book, then it is permitted to have this e-book open on your own computer during the exam and the appendix on “Input-Output” models. It is not permitted to have other documents open.
Own notes has to be printed out on paper. It is not allowed to your own notes open on your computer during the exam.
If the assignment is written by use of a digital pen then it is allowed to use the software accompanying the digital pen or the program SDUscribble.
The assignment can be written by hand, and then be digitally transferred by use of a hand scanner. It is allowed to use the software accompanying the hand scanner.
The assignment can be written by hand and then being photographed by use of a digital camera (not Ipads/tablets/smartphones). The files of the photo images can then be transferred to the Word-template.
The memory of the digital pen, the hand scanner and the digital camera has to be empty/cleared before the start of the exam.
All handmade graphs, formulas and similar has to transferred to the Word-template before the end of the exam.
EKA
B100104X12
B100104412
B100104112
B100104412
B100104112
Exam - 2nd semester
Name
Exam - 2nd semester
Timing
Exam: June.
Reexam: August.
Exam on the spring topics.
The examination is intended to demonstrate the student's ability to analyse and interpret a large-scale data set. Use of IT is included as an integral element of the solution.
Examination form at the re-exam can be changed.
Rules
-3 is not allowed
Tests
Exam
Name
Exam
Form of examination
Take-home assignment
Censorship
Second examiner: None
Grading
7-point grading scale
Identification
Student Identification Card - Exam number
Language
English
Duration
48-hours take-home exam.
Length
No limit.
Examination aids
All exam aids allowed.
Assignment handover
The assignment is handed out via the course page in Blackboard on the day of examination at 12 noon.
Assignment handin
Hand-in in SDUassignment in the course page in Blackboard.
ECTS value
5
Additional information
Internet access: Required.
EKA
B100104X02
B100104402
B100104102
B100104402
B100104102
External comment
NOTE - This course is identical with the former course 83204x01 / Odense: Autumn: 83204301 Spring: 83205301 Sønderborg:
Autumn: 83204501 Spring: 83205501 Mathematics and Statistics.
Used examination attempts in the former identical course will be transferred.
Courses that are identical with former courses that are passed according to applied rules cannot be retaken.
The student is automatically registered for the first examination attempt when the student is registered for a course or course element with which one or more examinations are associated. Withdrawal of registration is not possible, and students who fail to participate in an examination have used one examination attempt, unless the University has made an exemption due to special circumstances.
If a student does not meet the established university prerequisites for taking the exam, he or she has used one examination attempt, unless the University has made an exemption due to special circumstances.
The overall grade is calculated as an average of both part-examinations with equal weights.
Previously passed part-examinations may be transferred.
The examination is intended to test the goal achievement on all the listed points.
The overall grade for the course is reached by adding together the two part grades. The part grades must not include the grade -3. The overall grade 02 cannot be achieved through rounding up. The part grade 00 cannot be improved if the overall grade 02 or above has been achieved.