Integrated Cours (IC)
Objectives
At the end of the course, students will acquire:
- The ability to manage research problems and datasets.
- The ability to perform the most common descriptive analyses and the main descriptive statistics and the principal hypothesis testing methods.
- The knowledge to use the R programming language and the R Studio software to produce short data analysis reports.
Syllabus
THEORETICAL PART
- Review of the Statistics I syllabus.
- t-test for paired data.
- Wilcoxon test.
- Multiple linear regression.
- One-way ANOVA (between and within).
- Kruskal-Wallis test and Friedman test.
- Factorial ANOVA (between, within, and mixed).
PRACTICAL PART
- Use of the `tidyverse` and `psych` package collections in R and R Studio.
- Graphical representation of data.
- Importing datasets from other formats.
- Use of main descriptive statistics.
- Application of hypothesis testing studied in Statistics I and Statistics II.
Exam
The achievement of the course objectives will be assessed through the production of a project using R and R Studio, along with a final written exam.
The evaluation will consist of:
- Practical test (project in Quarto or R Markdown format with the analysis of a dataset provided by the instructor) – to be submitted at least one week before the written exam and a prerequisite for admission.
- Oral discussion of the practical test.
- Written exam on Moodle consisting of 30 multiple-choice questions with 4 answer options, only one of which is correct (passing grade with 18 correct answers).
Bibliography
Welkowitz, J., Cohen, B., Ewen, R. (2013). Statistica per le scienze del comportamento. Maggioli Editore.
