Data analysis (2019/2020)

Course code
Name of lecturer
Margherita Pasini
Margherita Pasini
Number of ECTS credits allocated
Academic sector
Language of instruction
Sem. 1B dal Nov 11, 2019 al Jan 11, 2020.

Lesson timetable

Go to lesson schedule

Learning outcomes

The course aims to provide students with an understanding of statistical concepts and the ability to conduct statistical analyses (using open source statistical packages) as used in psychological research. Topics include descriptive statistics, inferential statistics and correlational models. Basic skills will be given in designing, executing, analysing, interpreting and reporting psychological research, mainly in the organizational context.

By the end of the course students will be able to:
- describe and use some techniques of data collection and data analysis in psychological educational research, and report and discuss the results;
- describe and use methods useful to assess the effectiveness of interventions;
- develop research design, mainly in the field of organizational and educational psychology.


- Describing data (measures of central tendency and dispersion)
- Normal distribution and z-scores
- Sampling distribution, and hypothesis testing, power, effect sizes
- Hypothesis tests applied to means: t-tests (for independent and related samples)
- Simple Analysis of Variance (for independent and related samples)
- Factorial Analysis of Variance (between, within, and mixed models)
- Correlation and Regression
- Categorical data and chi-square
- Hierarchical regression and moderation analysis

Reference books
Author Title Publisher Year ISBN Note
Dennis Howitt, Duncan Cramer Introduzione alla statistica per psicologia. Con MyLab. Con e-book. Con espansione online. Pearson Education Italia 2014 9788865183847
J. Welkowitz, B. Cohen, R. Ewen Statistica per le scienze del comportamento Apogeo Education 2009 9788850328635

Assessment methods and criteria

The starting point is a written exam. The use of the PC is needed, particularly the use of spreadsheets (Microsoft Excel, free for students, or Apache OpenOffice Calc) and of JASP, an open source statistical package. Starting from a given dataset, students should perform some analysis in agreement with the program of the course. 5.6 Exercises will be proposed, each scored on a 6/7 points scale, depending on the difficulty, on the bases of a 32-point score. On the basis of the results in this written exam, the teacher can decide for an interview.