Statistics I for Business Economics

6 ECTS credits
160 h study time

Offer 2 with catalog number 1010744ANR for all students in the 2nd semester at a (A) Bachelor - preliminary level.

Semester

2nd semester

Enrollment based on exam contract

Impossible

Grading method

Grading (scale from 0 to 20)

Can retake in second session

Yes

Taught in

Dutch

Faculty

Faculty of Social Sciences & SolvayBusinessSchool

Department

Applied economics

Educational team

Luc Hens (course titular)
Achtee Al Yussef

Activities and contact hours

26 contact hours Lecture
26 contact hours Seminar, Exercises or Practicals
121 contact hours Independent or External Form of Study

Course Content

This course covers descriptive statistics (the art of summarizing data) and introduces the student to inferential statistics (the art of using sample data to make numerical conjectures about problems involving a population). We learn how to display data in tables and charts (frequency tables, histograms, boxplots, time series plots, …); how to describe the shape of data distributions and summarize their center and spread (mean, median, standard deviation, interquartile range, …); and how to display and summarize and interpret the relationship between two variables (scatter plots, correlation, line of best fit). We then learn about the basic elements of probability needed for statistical inference (probability rules, joint and conditional probability, contingency tables, probability trees,…); about random variables (expected value and standard error; probability models). Finally, we study the sampling distributions of proportions and means and use the Central Limit Theorem to construct confidence intervals for population proportions and population means.

Course material

Handbook (Required) : Business Statistics, Sharpe, N. R., De Veaux, R., and Velleman, P., 3de editie, Pearson Education, 9781292058696, 2015
Digital course material (Required) : Studiewijzer voor Statistiek voor de Bedrijfseconomische Wetenschappen I, Luc Hens, 2021
Practical course material (Required) : Formuleblad voor Statistiek voor de Bedrijfseconomische Wetenschappen I, Luc Hens, 2021
Digital course material (Required) : R: A language and environment for statistical computing, R Development Core Team, R Foundation for Statistical Computing, 2021
Practical course material (Required) : Texas Instruments TI-84 Plus CE-T wetenschappelijke rekenmachine
Digital course material (Required) : RStudio Desktop (Open Source Edition), RStudio Team, RStudio, 2021

Additional info

Not applicable.

Learning Outcomes

General competences

This course aims at providing you with an understanding of descriptive statistics (displaying and describing data) and inferential statistics (making valid generalizations from sample data).

At the end of the course, you are able to:

distinguish between categorical and quantitative data, and display and describe categorical and quantitative data;
compute and interpret a coefficient of correlation and the line of best fit;
apply the rules of probability;
work with random variables and probability models (binomial model, normal model, …);
explain the properties of the sampling distribution of a proportion or a mean (and the conditions under which those properties hold);
find (if appropriate) a confidence interval for a proportion or a mean using data from a large sample, and interpret the meaning of the confidence interval;
explain the limitations of statistical methods;
use statistics in an ethical way;
use statistical software and a scientific calculator to do statistical computations (enter data, generate descriptive statistics and graphs, compute probabilities of normally distributed random variables; compute confidence intervals);
communicate the results of statistical work; more specifically, write up the results of statistical analysis in a report consisting of a non-technical abstract aimed at decision makers, so that they can improve their decisions, and a main section aimed at peers explaining the technical details and exact interpretation of the results. The report is formatted in APA Style.

Grading

The final grade is composed based on the following categories:
Written Exam determines 90% of the final mark.
Other Exam determines 10% of the final mark.

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

Written Exam with a relative weight of 90 which comprises 90% of the final mark.

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

Paper (group) with a relative weight of 10 which comprises 10% of the final mark.

Additional info regarding evaluation

You cannot redo the group paper for the second examination session; in the second examination session you keep the grade for the paper obtained during the semester.

Carefully check the course syllabus (posted on the learning platform) for the deadline to submit the paper.

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