At the end of the course, students will have attained knowledge and tools that are useful for describing the data and making statistical inference in psychology. Moreover, they will be able to identify the appropriate statistics for addressing specific research questions, to apply them, and to interpret the results will be evaluated.
Course Prerequisites
There is no prerequisite.
Teaching Methods
Teaching will take place through lectures, practical exercises, and laboratory, with a focus on discussion and dialogue with the students, also with the use of slides.
Assessment Methods
The exam consists of a written test. The test includes 31 forced-choice questions, to be solved in 40 minutes, which will permit to verify if the student has learnt the theoretical foundations and to assess his or her ability to apply the theoretical knowledge to real life problems concerning specific research and intervention contexts. It will be assigned one point for each correct answer. The final mark is the sum of the scores assigned to each question. Students who will provide correct answers for all the questions will obtain the maximum mark (30 cum laude). The marks will be sent to the institutional email of each student through the University information system.
Contents
The course will present an overview of the main arguments linked to introduction to probability, and basic statistical inferential methods of data analysis. Specifically, the following topics will be covered: tests for mean difference (single sample, independent samples, paired samples), chisquare test (equiprobability, independence, test of a model), linear correlation and linear regression.
The students not attending classes and the working students must adhere to the program described above. For any request, they can contact the professor either personally or by e-mail.
