Statistical Data Analysis
Statistical data analysis is a pervasive issue especially nowadays when we are experiencing the Big Data revolution. “The evidence is clear: Data-driven decisions tend to be better decisions. Leaders will either embrace this fact or be replaced by others who do” says Andrew McAfee the co-director of the Initiative on the Digital Economy in the MIT Sloan School of Management. Knowledge on how to treat data is thus an essential requirement in many master courses and Digital Fashion Communication is not an exception to this rule. In this course, I will provide the students with an introduction to statistical thinking, to the principles of inductive reasoning and to a data driven approach to decision making. This will require understanding the logic behind statistical methods and techniques, acquiring skills on how to reproduce them in a friendly software environment and interpreting the results of the analysis
- Understanding the logic of the quantitative approach
- Familiarize with main concepts in probability and statistics
- Being introduced to descriptive and inferential methods
- Traditional lectures.
- Laboratory guided sessions
Although not compulsory, due to the nature of the topics treated and the need of assistance during the practical laboratories, attendance is highly recommended for all students.
The final exam will be a written online test in English
To answer the final test’s questions, it will be necessary to perform some calculation with the dedicated software introduced in the course.
Required materials for passing the exam:
- Lectures’ slides
- Video tutorial
Optional material for a better understanding of the topic:
- Field, A. (2000) Discovering Statistics Using SPSS, Sage Publishers.
- Field, Andy. Discovering Statistics Using SPSS,. Sage, 2000.
- Master of Science in Communication and Economics in Corporate Communication, Lecture, 1st year
- Master of Science in Digital Fashion Communication, Lecture, 1st year