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Data analysis

Descrizione

Course Objectives

By the end of the course, students will have learned how to:

  • Identify (research) questions that can be answered with statistical data analysis;
  • Assess the appropriateness of various data-analytical techniques in response to these questions;
  • Report basic descriptive statistics, including graphical representations;
  • Conduct basic statistical analyses, including univariate, bivariate, and multivariate statistics;
  • Use basic Excel functions;
  • Use basic SPSS functions;
  • Read and present statistical results;
  • Develop their own research question and select appropriate measures and analytical procedures

Course Description

This course introduces students to the statistical analysis of empirical data to answer driving questions and test scientific hypotheses in social sciences. The course is designed to provide students with several fundamental skills, which will be helpful for their future course work, Master thesis and/or job tasks, considering that basic data management and analytical skills are increasingly requested in today’s labor market.  The course alters front lectures with individual assignments and exercises.

Learning Methods

During the lessons, principal statistical concepts, definitions, and procedures will be introduced. Alongside, practical exercises underlying the most common statistic procedures will be covered in class. In particular, students will be guided on how to use statistical software such as Excel and SPSS.

Attendance

This course requires regular attendance (at least 80%), every lesson is meant to be propaedeutic for the subsequent one.   

Examination Information

The final grade is composed of:

  • Individual assignments carried out during the course (10%)
  • Single oral paper presentation (10%)
  • Written exam (80%)

Required Material

All material presented in class will be available on iCorsi3.

Reference book:

  • Gravetter, F., & Wallnau, L. (2012). Statistics for Behavioral Sciences. Belmont, CA: Wadsworth Cengage Learning.

Persone

 

Schulz P. J.

Docente titolare del corso

Marciano L.

Assistente

Informazioni aggiuntive

Semestre
Autunnale
Anno accademico
2021-2022
ECTS
6
Lingua
Inglese