Introduction to Statistics
Study Board of Business Economics
Teaching language: English
EKA: B220024402
Censorship: Second examiner: None
Grading: 7-point grading scale
Offered in: Soenderborg
Offered in: Spring
Level: Bachelor
Course ID: B220024401
ECTS value: 5
Date of Approval: 18-09-2020
Duration: 1 semester
Course ID
Course Title
Teaching language
ECTS value
Responsible study board
Date of Approval
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Recommended prerequisites
Aim and purpose
The objective of this course is to provide the student with statistical tools for solving problems within the area of business administration. The objective is also to give the student an understanding of the interaction between statistics and economic problems.
The course 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 advertises 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.
Discrete and continuous distributions
Confidence intervals and hypothesis testing for
Descriptive statistics
•Selection of samples - simple random method
•Central tendency, variation, skewness and extremes
Discrete and continuous distributions
•Including Binomial, Poisson and Normal distribution
•Variance-covariance of a set of stochastic variables
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
Description of outcome - Knowledge
To apply statistical methods and tools on frequently occurring issues within the fields of business and economics.
Description of outcome - Skills
- To be able to describe, analyze and interpret a statistical dataset by use of statistical applications or packages like for example the add-in “Analysis Tool Pack” to Excel or the add-in “Megastat” to Excel
- To be able to apply statistical methods in order to investigate issues in sociology, business and economics including to analyze specific issues by use of a given dataset
- To be able to describe relevant parts of the dataset by descriptive statistical tools
- To be able to formulate hypotheses onrelevant relations known from business and economics-To be able to select and apply relevant methods in order to examine and evaluate the validity of statistical hypotheses-To be able to provide a relevant interpretation of the applied analyses in a written context
Description of outcome - Competences
To be able to discuss the assumptions and limitations of the selected statistical methods, and to validate the applied statistical method relative to the issued being addressed.
Literature
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 or similar 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
Scheduled classes:
2 lectures and 2 exercise sessions per week for 15 weeks.
Workload:
Students will be required to do 135 hours of work, which is expected to be spent as follows:
•Lectures: 30 hours
•Lectures: 30 hours
•Exercise sessions: 30 hours
•Preparations for exercise sessions and lectures: 50 hours
•Take home assignment: 25 hours.
Examination regulations
Exam
Name
Exam
Timing
Exam: June.
Reexam: August.
For students taking the course as a supplementary course after admission to the master's program the following applies:
The student must pass the exam no later than 6 months after commencing his/her studies
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
Digital hand-out via "Digital Exam".
Assignment handin
Digital submission via "Digital Exam".
ECTS value
5
Additional information
Examination form may be altered for the reexamination.
A change in the examination form will be announced no later than 14 days prior to the re-exam.
EKA
B220024402
External comment
NOTE - This course is identical with the former course 83306301 Supplementary course in 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.
Courses offered
| Offer period | Offer type | Profile | Education | Semester |
|---|---|---|---|---|
| Spring 2021 | Mandatory | Supplering - alle byer / E19 - F20 - E20 - F21 - E21 - F22 - E22 | Bachelor of Science in Economics and Business Administration | Bachelor of Science (BSc) in Economics and Business Administration | Esbjerg, Soenderborg, Slagelse, Odense, Kolding | Spring 2021 | Exchange students |