1. Sample size and Statistical Inference
2. Introduction to Desing of Experiments
3. Factorial Experiments
4. Screening Experiments
5. Response Surface Experiments
6. DOE Guidelines
7. Sampling techniques
Participation in classes and exercises proposed during and after the sessions. The student will pass the course if: 1) they have attended 80% of the sessions, 2) they have delivered all exercises on time and 3) have a rating of 5 or more in delivered exercises.
Final grade: "Pass" or "Fail".
To obtain a "Pass" grade:
• Attendance of 80% or more of the classes is required (attendance will be recorded).
• Completion of exercises proposed during and after the sessions is required, demonstrating the knowledge acquired. These will be assessed by the teaching staff.
Use of Artificial Intelligence (AI) in the Course
The use of AI tools is allowed with limited and responsible use. Specifically, AI may be used for the following tasks:
• Searching for information related to statistical concepts or practical applications.
• Generating an initial draft of explanatory texts or answers.
• Improving spelling, grammar, and clarity of written texts.
• Translating text between languages.
• Reviewing answers before submission.
• Generating R code, provided the code is understood and reviewed by the student.
Permitted tools include:
ChatGPT, Gemini, Claude, GitHub Copilot, DeepL, Grammarly, among others.
Conditions of use:
• You must explicitly state which AI tools were used.
• You must document the prompts used, the responses received, and briefly describe the process followed to revise and edit the AI-generated content.
Example of citation:
“ChatGPT was used to generate a draft response to question 3. The prompt used was: ‘Explain how to calculate the confidence interval for a proportion in R.’ The response was reviewed, simplified, and adapted to the context of the exercise.”
Not allowed:
• Using AI tools to automatically generate full answers to assignments without your own understanding or critical review.
• Using AI tools to avoid practicing or engaging with the material, which is essential for your learning and progress in the course.
Criteris específics de la nota «No Presentat»:
A student will be considered "No Presentat" if they have attended less than 80% of the classes or have not completed the assessment assignments.
Avaluació única:
Single assessment ("avaluació única") is not available for this course.
Requisits mínims per aprovar:
Rating of 5 or more in delivered exercises