All programmes > Statistics and Data Management

Statistics and Data Management (B-KUL-T2ASD2)

6 ECTSEnglish61 Second termCannot be taken as part of an examination contract
Vanrumste Bart (coordinator) |  Desmet Stef |  Vanrumste Bart |  Cuyx Bram (cooperator) |  Vinckier Nigel (cooperator)
OC Polyvalente Ingenieursvorming - Campus Groep T Leuven

Aims

Learning outcomes:

  • K1: Possess basic scientific-disciplinary knowledge and understanding
  • I1: Analyse and solve problems
  • I3: Application-oriented research
  • P1: Operationalisation
  • G2: Communicating with peers and non-colleagues
  • G3 Critical reflection

 

Objective:

Conceptual knowledge

  • The student has knowledge of concepts from descriptive statistics.
  • The student knows and understands basic concepts of statistics, such as distribution, tests of hypothesis, observed significance, ...
  • The student knows the relevant parts and aspects of databases.

Procedural knowledge

  • Starting from a set of data, the student can perform statistical calculations, structure data and visualise it.
  • The student can translate a real-world problem into a statistical test based on a (large) group of data. He/she can carry out this test and formulate motivated decisions.
  • The student can perform basic operations on a database, such as design, development, adding data, querying a database, ...

Previous knowledge

The student has the basic knowledge of mathematics and computer science.

Order of Enrolment

Mixed prerequisite:
You may only take this course if you comply with the prerequisites. Prerequisites can be strict or flexible, or can imply simultaneity. A degree level can be also be a prerequisite.
Explanation:
STRICT: You may only take this course if you have passed or applied tolerance for the courses for which this condition is set.
FLEXIBLE: You may only take this course if you have previously taken the courses for which this condition is set.
SIMULTANEOUS: You may only take this course if you also take the courses for which this condition is set (or have taken them previously).
DEGREE: You may only take this course if you have obtained this degree level.


FLEXIBLE(T1ACD1) OR FLEXIBLE(T1ACD2)

The codes of the course units mentioned above correspond to the following course descriptions:
T1ACD1 : Computationeel denken
T1ACD2 : Computational Thinking

This course unit is a prerequisite for taking the following course units:
T2VPT1 : Programmeertechnieken
T2VPT2 : Programming Techniques
T3WDE1 : Data engineering
T3WDE2 : Data Engineering
T3CEC2 : Chemical Engineering Computing
T3POM2 : Operations Management
T3WSU2 : Management Skills
T3POM1 : Operations management
T4OML1 : Machine learning (EM)
T4ATQ1 : Total quality management
T4OML2 : Machine Learning (EM)
T4ATQ2 : Total Quality Management
T4VML1 : Machine learning (EA)
T4VML2 : Machine Learning (EA)
T4UMM2 : Manufacturing Metrology

Identical courses

This course is identical to the following courses:
T2ASD1 : Statistiek en databeheer
B3074R : Statistiek en databeheer
JPI0ZN : Statistiek en databeheer (schakel) (No longer offered this academic year)
ZA0184 : Statistiek en databeheer
YI1387 : Statistiek en databeheer
JPI0VK : Statistiek en databeheer

Is included in these courses of study

Activities

2.5 ects. Statistics: Lecture (B-KUL-T2hSD2)

2.5 ECTSEnglishFormat: Lecture23 Second term
Vanrumste Bart
OC Polyvalente Ingenieursvorming - Campus Groep T Leuven

Content

The central concept in this section is hypothesis testing. Here, in addition to the construction and execution of the hypothesis tests, students also learn how to interpret the various parameters.

A/ General concepts of probability

  • Meaning of the concept of probability and its rules: union of events, complementarity events, conditional probability of events (Bayes).
  • Concepts related to random variables: discrete and continuous random variables, probability mass function and probability density function, characteristic numbers in a probability distribution
  • Special discrete and continuous probability distributions
  • Sampling distributions

B/ From sample to confidence interval of a population parameter

  • The notion of confidence interval and confidence level
  • Confidence intervals of population parameters when using large and small samples
  • Confidence intervals for comparing two population parameters when using unpaired and paired samples
  • Determining sample size

C/ Testing of hypotheses

  • Basic principles of hypothesis testing: significance level, type I and type II errors
  • Statistical tests on a population parameter when using large and small samples
  • Statistical tests for comparing two population parameters when using unpaired and paired samples

D/ Capita Selecta

  • Regression: linear and non-linear
  • ANOVA tests
  • Design of experiments
  • Testing of probabilistic models
  • Chi-square test for independence
  • Non-parametric tests
  • Examination of statistical methods through simulation

 

Course material

Handbook: "Statistics" James McClave Terry Sincich - XXth edition or higher- Published Pearson.
Toledo: extra learning material, including ppt-slides, extra exercises and video recordings.

Format: more information

Flipped classroom

The theory is addressed in lectures and video recordings.

1.5 ects. Data Management: Lecture (B-KUL-T2hDB2)

1.5 ECTSEnglishFormat: Lecture14 Second term
Desmet Stef |  Vanrumste Bart
OC Polyvalente Ingenieursvorming - Campus Groep T Leuven

Content

A. Basic principles of databases.

Data model creation: ER diagrams

Database Management System

Simple create tables: entities, attributes, primary keys, foreign keys

SQL

Retrieve data from a single table:

Efficiently structure data in multiple tables:

Normalization

Selects on multiple tables

B. Principles of data processing.

Visualization of data

Privacy - GDPR

Principles of Data Mining, OLAP and Machine Learning

Course material

 Material on Toledo

online SQL training tool https://labtools.groept.be/sql/

2 ects. Statistical Data Management: Lab Session (B-KUL-T2pSD2)

2 ECTSEnglishFormat: Practical24 Second term
Vanrumste Bart |  Cuyx Bram (cooperator) |  Vinckier Nigel (cooperator)
OC Polyvalente Ingenieursvorming - Campus Groep T Leuven

Content

Putting into practice knowledge of data management and statistics.

Practising classical statistical concepts and hypothesis testing

Handling databases, working out practical examples of databases, tables and SQL queries

Working with issues that link both domains; extracting data, solving, interpreting and visualising integrated issues.

 

Course material

 Content on Toledo

Format: more information

Computer session

Evaluation

Evaluation: Statistics and Data Management (B-KUL-T72095)

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

Explanation


This OPO (Educational Unit) has only one published partial grade. Consequently, this partial grade is also the final grade.

The sole partial grade is determined based on three evaluation components:

Statistics: 40%
Data management: 30%
Statistical data processing: 30%

A form of guessing correction is applied to multiple-choice questions.

Absences:

In case of absence during the examination period, you must notify the examination ombudsman on the same day.

Information about retaking exams

The modalities are the same as in the first exam period.