Statistics II for Business Economics

6 ECTS credits
179 h study time

Offer 2 with catalog number 1009724BNR for all students in the 2nd semester at a (B) Bachelor - advanced level.

Semester

2nd semester

Enrollment based on exam contract

Impossible

Grading method

Grading (scale from 0 to 20)

Can retake in second session

Yes

Enrollment Requirements

Je hebt ‘Statistiek I voor Bedrijfseconomische Wetenschappen’ gevolgd, alvorens 'Statistiek II voor Bedrijfseconomische Wetenschappen’ op te nemen.

Taught in

Dutch

Faculty

Faculty of Social Sciences & SolvayBusinessSchool

Department

Business Technology and Operations

Educational team

Ona Van den bergh
Ineke van Gremberghe (course titular)

Activities and contact hours

39 contact hours Lecture
56 contact hours Seminar, Exercises or Practicals
84 contact hours Independent or External Form of Study

Course Content

Statistical analysis, also known as inferential statistics, aims to make conclusions which are valid for the entire population starting from a part of the population (a sample).
Since sampling is a random process, a call is to be made on probability theory to allow for generalisation based on the observation of a sample.
The classical one- and two-dimensional tests from statistical analysis (confidence intervals and hypothesis tests concerning the averages, variances, percentages, distribution and independency tests) are elaborated in more detail as well in this course. The most important tests from parametric as well as from non-parametric statistics are discussed.

Course material

Handbook (Required) : Business Statistics, Sharpe, N. R., De Veaux, R. and Velleman, P., 4de Global edition, Pearson Education, 9781292269313, 2021
Practical course material (Required) : Syllabus voor Statistiek voor de bedrijfseconomische wetenschappen II - 2022-2023, Vanhaverbeke, L., Canvas
Practical course material (Required) : Formuleblad voor Statistiek voor de bedrijfseconomische wetenschappen II, Vanhaverbeke, L., Canvas

Additional info

Not applicable.

Learning Outcomes

General competencies

In the framework of statistics and probability theory to:

give the student basic knowledge within the field of human sciences
lead the student to a critical attitude
initiate the student to be confident with new scientific knowledge
initiate the student to independent scientific research
learn the student to use recent informatic tools (software R) in collecting and treating information
learn the student to understand mechanisms and relations

Upon successfully completing this course:

The student will have a broad knowledge of statistics as a discipline and a good understanding of the domain of parametric and non-parametric statistics.
The student will be able to apply these methods to various decision-making problems (including those in the context of business and economics) by selecting the appropriate statistical method, applying it, and interpreting and explaining the results.
The student will be able to evaluate whether a certain method can be applied in a given context by checking assumptions and conditions.
The student will understand how the basic statistical tests and models covered in the course are constructed (including z-tests, t-tests, Chi-square tests, linear regression, non-parametric tests).
The student will be able to apply statistical methods for scientific research, which contributes to conducting independent scientific research in the context of the masterthesis.

Grading

The final grade is composed based on the following categories:
Written Exam determines 100% of the final mark.

Within the Written Exam category, the following assignments need to be completed:

Intermediate tests with a relative weight of 10 which comprises 10% of the final mark.
Obligatory written exam with a relative weight of 90 which comprises 90% of the final mark.

Note: the mandatory written exam consists of 2 parts: closed book for theorie, open book for exercises

Additional info regarding evaluation

Both the intermediate tests and the obligatory written exam will be conducted using multiple-choice questions. The obligatory written exam will be graded by positive scoring using a higher pass mark (standaard setting). This means that no points will be deducted for a wrong answer. However, guessing will be taken into account in the final grade by increasing the passing grade. The exact passing grade for the exam will be communicated in due time.

For the intermediate tests, a 10% point deduction per day will be applied for late submissions.

To pass this course component, the student must pass (i.e. score at least half of the points) on the exam component "obligatory written exam". This requirement does not apply to the intermediate tests.

Absence from the obligatory written exam will result in absence for the overall assessment.

The score obtained in the first session for the intermediate tests will also apply to the second session. It is not possible to retake the intermediate tests in the second session.

Partial exemption from the course material or partial transfer of grades to the next academic year is not possible.

Allowed unsatisfactory mark

The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context