All programmes > Statistics for Business (B)

Statistics for Business (B) (B-KUL-HSA10A)

6 ECTSEnglish78 First term
Dierckx Goedele (coordinator) |  Dierckx Goedele |  Boeckx Eric (cooperator)
OC Business Administration FEB Campus Brussel

Aims

5.a       Uses static and dynamic models, graphically and algebraically, to analyse and solve (business) economic problems.

             Defines probabilistic models and tests the quality of probabilistic frameworks to model economic problems.

5.b       Uses descriptive and inferential statistical methods and techniques to solve (business) economic problems.

             Applies descriptive statistical methods. Uses confidence intervals and hypothesis testing for parameters of 

             distributions to solve economic problems.

5.c       Studies and interprets associations between variables using linear regression techniques.

 

6.c       In line with the given practical relevance and the definition of the (business) economics problem, chooses and uses

             the appropriate techniques to acquire, analyse and interpret data.

             Chooses and uses appropriate descriptive statistics and appropriate inferential statistics to analyse and interpret

             data

6.e       From qualitative and quantitative research findings, draws scientific conclusions that bear practical relevance.

 

 

 

Previous knowledge

No prior knowledge is required for this course

Identical courses

This course is identical to the following courses:
Y00266 : Statistiek voor bedrijfswetenschappen (S)
HSH89A : Statistiek voor bedrijfswetenschappen (S)
HTH85A : Statistiek voor bedrijfswetenschappen (BL)

Is included in these courses of study

Activities

6 ects. Statistics for Business (B) (B-KUL-HSA10a)

6 ECTSEnglishFormat: Lecture78 First term
Dierckx Goedele |  Boeckx Eric (cooperator)
OC Business Administration FEB Campus Brussel

Content

Chapter 1 : Case study
-    Research questions
-    Case study: statistical literacy

Chapter 2: Sampling
-    Sampling methods
-    data classification (qualitative - quantitative; discrete - continuous; univariate - multivariate)

Chapter 3: Descriptive Statistics for one and more variables
-    Categorical data: frequency tables,  bar plots
-    Numerical data: histograms, empirical distribution function, quantiles, mean, standard deviation, median, interquartile range, robustness against outliers, transformation
-    Relationships between variables: scatterplot and correlation coefficient, time plot, contingency table and segmented bar plot

Chapter 4: Probability theory
-    Experimental probability: law of large numbers
-    Rule of Laplace
-    Rules for probability: complement rule, sum rule, multiplication rule
-    Conditional probability

Chapter 5: Distributions of random variables
-    Random variables
-    Discrete distribution: probability distribution, expectation, variance
-    Continuous distribution: density, expectation, variance
-    Transformations and linear combinations of random variables
-    Normal distribution
-    Binomial distribution

Chapter 6: Foundations for inference
-    Variability in estimates : sampling distribution, standard error
-    Sampling distribution for the mean: central limit theorem
-    Confidence interval for mean (variance known)
-    Hypothesis testing: null hypothesis, test statistic, p-value, type 1 and type 2 error, power, critical region
-    Hypothesis testing for mean (variance known)

Chapter 7: Inference for numerical data

-    t-test for one mean

-    t-test for paired data

-    t-test for difference of two means

-    ANOVA test

-    test for correlation

-    assumptions for parametric tests

 

Chapter 8: Inference for categorical data

-   test for single proportion

-   Chi square test for independence  in two-way tables

 

Chapter 9: Simple linear regression

-   Model specification

-   Inference for linear regression

-   Goodness of fit

-   Assumptions

 

Course material

Course material available on Toledo

http://webapps.odisee.be/Ancor/SSM/Pages/BekijkSSM.aspx?OID=22817

Format: more information

The course consists of a combination of formal lectures, learning conversations and collective work. During the formal lectures the most important concepts will be explained and illustrated by means of examples. Students are expected to participate actively during these lectures. Regularly a tutorial will be organised during which difficult exercises from the syllabus will be dealt with. SPSS will be introduced in these tutorials.
Doing exercises is an essential part in order to be successful. Exercises will be placed at the students' disposal on Toledo. As a result, the students will be able to evaluate their knowledge of the matter by means of the solutions. Exercises not dealt with in lectures and tutorials may be handed in, in order to be corrected.

Evaluation

Evaluation: Statistics for Business (B) (B-KUL-H74940)

Type : Exam during the examination period
Description of evaluation : Written
Type of questions : Open questions
Learning material : List of formulas, Calculator, Computer

Explanation


Evaluation caracteristics

Students will be evaluated on the basis of a written exam.
The exam consists of exercises similar to those of the syllabus and those dealt with in class and some theoretical questions. It is important to notice that the exercises' level of difficulty on the exam will be higher than those made in class/of the syllabus. At the beginning of the learning process rather easy exercises will be made compared to those of the exam. Students are expected to have a thorough command of theory . A good insight into the concepts and methods dealt with is essential in order to make the exercises on the exam.
For (part of) the exam, students will have a computer at their disposable. Students are allowed to use the programs SPSS/Excel.

A formula sheet will be provided during the exam. The content of this formula sheet is available on Toledo.
An example of the exam will be placed at the students' disposal at the end of the semester. It will be posted on Toledo.

Second exam opportunity

The evaluation methods during the first and second exam opportunities are identic.