6 ECTS credits
179 h study time

Offer 1 with catalog number 1021582BNR 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
Students must have taken 'Statistics for BE I', before they can enroll in this course. ​
Taught in
English
Faculty
Faculty of Social Sciences & SolvayBusinessSchool
Department
Business Technology and Operations
Educational team
Lieselot Vanhaverbeke
Dennis Verbist
Ineke van Gremberghe (course titular)
Activities and contact hours
39 contact hours Lecture
56 contact hours Seminar, Exercises or Practicals
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, (same book as used for the course Statistics for Business and Economics I), Sharpe, N. R., De Veaux, R. and Velleman, P., 4rd Global Edition, Pearson Education, 9781292269313, 2021
Practical course material (Required) : Syllabus for Statistics for Business and Economics II - 2020-2021, Vanhaverbeke L., Canvas
Practical course material (Required) : Formula sheet for Statistics for Business and Economics II, Vanhaverbeke L., Canvas
Practical course material (Required) : Texas Instruments TI-84 Plus CE-T wetenschappelijke rekenmachine
Practical course material (Required) : RStudio Desktop (Open Source Edition), RStudio Team, RStudio
Additional info

Not applicable.

Learning Outcomes

General competences

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 90% of the final mark.
SELF Practical Assignment determines 10% of the final mark.

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

  • Obligatory written Exam with a relative weight of 90 which comprises 90% of the final mark.

    Note: Multiple choice questions (higher pass mark)

Within the SELF Practical Assignment category, the following assignments need to be completed:

  • Intermediate Tests with a relative weight of 10 which comprises 10% of the final mark.

    Note: Late submission will be subject to a 10% point deduction per day.

Additional info regarding evaluation

The obligatory written exam will be graded by multiple choice questions by positive scoring using a higher pass mark (higher cut-off point). 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 pass mark. The exact pass mark 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 the student must score at least half on the overall assessment for this course.

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

This offer is part of the following study plans:
Bachelor of Business Economics: Year 1 and 2
Bachelor of Business Economics: Year 3: Orientation Business and Technology
Bachelor of Business Economics: Year 3: Orientation International Business
Preparatory Programme Master of Science in International Business: Default track
Preparatory Programme Master of Science in Business Engineering: Business and Technology: Default track