Dades generals
-
Curs acadèmic:
- 2026
-
Descripció:
- L'objectiu principal d'aquest curs és que els estudiants que estan realitzant el doctorat a la UdG puguin començar a analitzar, des del punt de vista estadístic, un conjunt de dades i obtenir conclusions recolzades en la metodologia presentada. Així mateix, els estudiants adquiriran una cultura estadística que els permetrà enfrontar-se a una lectura crítica inicial d'articles científics. Tots els conceptes presentats en el curs es tractaran de forma pràctica amb un programari específic d'anàlisi de dades.
Introducció al programari estadístic. Lectura de dades i operacions amb variables. Descripció de dades unidimensionals. Descripció de dades bidimensionals. Mesures d'associació. Introducció a la inferència estadística. Estimació i contrastos. Ajust en models de regressió. Regressió lineal i regressió logística.
El curs és optatiu i es pot cursar l'any acadèmic escollit pel doctorand, tant si cursa el doctorat a temps complet com a temps parcial.
-
Crèdits:
- 1
-
Professor responsable:
- Marc Saez Zafra
Grups
Altres Competències
- CG1- Select and systematize the information efficiently
CG2- Communicate orally and in writing on topics of their specialty in an original and creative way, adapting to the audience or the recipients (expert and non-expert audiences) and using the supports and / or resources that make them more effective oral and written productions
CE4- Use the appropriate sources of information to update knowledge on advances in research and on methods and proposals for intervention
CG4- Critically analyze the data and know how to interpret and extract significant results
CG7- Formally express the relationships between the variables involved in a problem, using the main computer, mathematical and statistical instruments to solve them
ECOCE4- Apply the basic tools of statistical inference and models.
Continguts
1. - Descriptive Statistics
- Bivariate inference
- ANOVA and regression models
- Confounding and modification of the effect
Activitats
|
Tipus d’activitat |
Hores amb professor |
Hores sense professor |
Hores virtuals amb professor |
Total |
| Sessió participativa |
40,00 |
0
|
10,00 |
50,00 |
| Sessió pràctica |
40,00 |
0
|
10,00 |
50,00 |
| Treball en equip |
0
|
20,00 |
0
|
20,00 |
|
Total |
80,00 |
20,00 |
20,00 |
120 |
Bibliografia
Avaluació i qualificació
Activitats d'avaluació:
|
Descripció de l'activitat |
Avaluació de l'activitat |
% |
Recuperable |
| Participation in face-to-face sessions |
Participation in face-to-face sessions, proportional grade on a scale of 0-40. |
40 |
No |
| Level of participation and discussion in the face-to-face sessions |
Level of participation and discussion in the face-to-face sessions, proportional grade on a scale from 0 to 40. |
40 |
No |
| Presentation and correction of the final course work |
Presentation and correction of the final course work, proportional grade on a scale of 0 to 20. |
20 |
No |
Qualificació
Grading criteria:
Final grade: “Pass” or “Not Pass”.
To obtain a “Pass” grade:
· You must attend 80% or more of the classes (attendance will be recorded).
· You must complete an assignment that demonstrates the knowledge acquired and that will be evaluated by the faculty.
Students will be graded according to the following parameters:
1. Participation in face-to-face sessions, proportional grade on a scale of 0-40.
2. Level of participation and discussion in the face-to-face sessions, proportional grade on a scale from 0 to 40
3. Presentation and correction of the final work of course, proportional note in a scale of 0 to 20.
The use of AI-based tools is permitted to perform exclusively these tasks:
- Information search.
- Improving the spelling, grammar and clarity of a text.
- Translating a text.
- Reviewing the answer.
In any case, it will be necessary to explain the following points:
- Cite the AI tools used in the preparation of the work.
- Specify the prompts that have been used.
- Specify the answer obtained
- Detail the process that has been followed to review and edit the answer.
Inappropriate use of AI, as well as failure to explain the required points, will be considered academic fraud.
Criteris específics de la nota «No Presentat»:
Any of the following conditions:
Not having participated mostly in the face-to-face sessions.
Failure to submit the final course project.
A student who has not attended at least 80% of the classes or who has not completed the evaluation assignment will be considered “Not Presented”.
Avaluació única:
There is no single assessment in this subject
Requisits mínims per aprovar:
To be considered to have passed the subject, a minimum grade of 5.0 must be obtained
Tutoria
e-mail to: marc.saez@udg.edu
Comunicació i interacció amb l'estudiantat
e-mail to: marc.saez@udg.edu
Modificació del disseny
Modificació de les activitats:
In a part-time classroom setting due to COVID-19:
The virtual adaptation of the subject does not imply any change in the evaluation criteria and the weighting of the activities described in the original design.
In a fully virtual classroom setting due to COVID-19:
The approach is the same, by videoconference through one of the platforms recommended by the University.
Modificació de l'avaluació:
In a part-time classroom setting due to COVID-19:
The virtual adaptation of the subject does not imply any change in the evaluation criteria and the weighting of the activities described in the original design.
In a fully virtual classroom setting due to COVID-19:
The approach is the same, by videoconference through one of the platforms recommended by the University.
Tutoria i comunicació:
In a part-time classroom setting due to COVID-19:
The virtual adaptation of the subject does not imply any change in the evaluation criteria and the weighting of the activities described in the original design.
In a fully virtual classroom setting due to COVID-19:
The approach is the same, by videoconference through one of the platforms recommended by the University.