Statistics Consultancy
Code: 104877 ECTS Credits: 6| Degree | Type | Year |
|---|---|---|
| Applied Statistics | OP | 4 |
Contact
- Name:
- Llorenç Badiella Busquets
- Email:
- llorenc.badiella@uab.cat
Teaching groups languages
You can view this information at the end of this document.
Prerequisites
Informatics Tools for Statistics
Linear Models 1
Linear Models 2
Advanced Modelling
Unsupervised Learning
Machine Learning 1
Aprenentatge Automàtic 1
Objectives and Contextualisation
Develop skills necessary to carry out professional consultancy tasks in statistics.
Covering the different fields of statistical consultancy:
- Health Sciences
- Banking and insurance
- Sociological studies and surveys
Learning Outcomes
- CM14 (Competence) Propose the statistical model needed to analyse data sets belonging to real studies.
- KM17 (Knowledge) Recognise the statistical models for the analysis of data with different structures and complexities that frequently appear in different fields of application.
- SM16 (Skill) Select appropriate sources of information for the statistical work.
- SM17 (Skill) Discuss scientific articles in which the analysis of a study of the different areas of application is considered.
- SM18 (Skill) Refine the information available for subsequent statistical processing.
- SM19 (Skill) Analyse complex data, whether this is due to their characteristics or their size.
Content
Introduction
- Objective of the Statistical Consulting
- Areas of Consultancy and Needs
- Functions and responsibilities of the Statistical Consultant
- Work meetings
- Objectives according to scope
- Budget
Statistical Report
- Summary Graphics Analysis
- Methodology
- Validation
- Presentation of results
Productive programming with SAS and / or R
- Syntax files structure
- Implementation of Statistical Techniques
- Functions to reproduce code
- Production of results
Practical cases
- Reports
- Presentation and Review
Activities and Methodology
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Directed | |||
| Practical cases | 15 | 0.6 | CM14, KM17, SM16, SM17, CM14 |
| Practical sessions | 30 | 1.2 | CM14, KM17, SM16, SM17, CM14 |
| Theory | 30 | 1.2 | CM14, KM17, SM16, SM17, SM18, SM19, CM14 |
The subject will follow the following methodology:
- Theoretical classes
- Practical software sessions
- Evaluation of practical cases
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Assessment
Continous Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| Oral Presentation | 40 | 35 | 1.4 | CM14, KM17, SM16, SM18, SM19 |
| Project 1 | 30 | 20 | 0.8 | CM14, KM17, SM16, SM17 |
| Project 2 | 30 | 20 | 0.8 | CM14, KM17, SM16, SM17 |
The course will be assessed through the resolution of various practical cases, which will be carried out either in groups or individually.
For each of these projects, the following documentation must be submitted:
Initial proposal
Preliminary report
Final results report
Finally, the results of the practical cases must be presented publicly.
This course does not allow for the single assessment modality.
Bibliography
Cabrera, J.; McDougall A. (2002). Springer-Verlag New York.Statistical Consulting
Statistical Rules of Thumb - Gerald Van Belle - Wiley Series in Probability and Statistics
Common Errors in Statistics (and How to Avoid Them) - Good, Hardin - Wiley
SAS and R: Data Management, Statistical Analysis, and Graphics - Kleinman , Horton - Chapman and Hall
SAS for Mixed Models, Second Edition - Little et al - SAS Publishing
Software
SAS, R, Python, Latex, Markdown, RShiny
Groups and Languages
Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.
| Name | Group | Language | Semester | Turn |
|---|---|---|---|---|
| (SEM) Seminars | 1 | Catalan | first semester | afternoon |
| (TE) Theory | 1 | Catalan | first semester | afternoon |