Introduction to Statistics

Study Board of Business Economics

Teaching language: English
EKA: B220024102
Censorship: Second examiner: None
Grading: 7-point grading scale
Offered in: Odense
Offered in: Spring
Level: Bachelor

Course ID: B220024101
ECTS value: 5

Date of Approval: 11-09-2018


Duration: 1 semester

Course ID

B220024101

Course Title

Introduction to Statistics

Teaching language

English

ECTS value

5

Responsible study board

Study Board of Business Economics

Date of Approval

11-09-2018

Course Responsible

Name Email Department
Nils Karl Sørensen nks@sam.sdu.dk

Offered in

Odense

Level

Bachelor

Offered in

Spring

Duration

1 semester

Mandatory prerequisites

None.

Recommended prerequisites

Mathematics level B from secondary school.

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 thus provides tools that are used in other subjects, for example Corporate Finance, Microeconomics, and QuantitativeAnalysis of Survey Data. 

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 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.

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 

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 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, the add-in Megastat or similar;
•To use statistical methods and analyses to investigate problems in economics and business economics, including - based on a specific 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

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.

________

Students will be required to do 135 hours of work, which is expected to be spent as follows:

•Lectures: 30 hours
•Exercise sessions: 30 hours
•Preparations for exercise sessions and lectures 50 hours
•Take home assignment (second part-examination): 25 hours.

Examination regulations

Exam

Name

Exam

Timing

Exam: June.
Reexam: August.

Examination form may be altered for the reexamination, eg. From written to oral examination.

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

B220024102

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.

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. 

Courses offered

Offer period Offer type Profile Education Semester

URL for Skemaplan