Social sciences and humanities
Subject: DATA ANALYSIS FOR DIGITAL MARKETING I (A.A. 2023/2024)
degree course in DIGITAL MARKETING
Course year  1 

CFU  6 
Teaching units 
Unit Unico
Statistics and Mathematics (lesson)

Exam type  written 
Evaluation  final vote 
Teaching language  Italiano 
Teachers
Overview
The course is aimed at introducing statistical reasoning, both in exploratory and inferential settings. At the end of the course, the student will be able to use the tools for exploratory data analysis, which consists in organizing, displaying and summarizing data, and the fundamentals of statistical inference, to explain how from a small set of observations it is possible to draw conclusions about the characteristics of a phenomenon. For further information on the aims of the course, please refer to the section expected learning outcomes.
Admission requirements

Course contents
Exploratory data analysis (3 CFU)
 Data, populations, variables, data sources
 Graphic representations and frequency tables
 Summaries of a statistical distribution: position and variability.
 Multiple distributions.
Probability (0.5 CFU)
 Random variables, definition, discrete and continuous distributions.
Statistical inference (2.5 CFU)
 Sample and population, sampling variability
 Sketch on Interval estimate
 Hypotheses testing for a mean and a proportion
 Linear regression model and analydìsis of variance.
Teaching methods
Lectures and practicals, also by using statistical software. Attendance is highly recommended. Classroom lessons will be recorded and made available on the ONELab platform of the Department of Communication and Economics. The course will be taught in Italian.
Assessment methods
The students’ evaluation will be based on a written exam. It will be possible to take an intermediate test in the November exam session corresponding to approximately 5060% of the program. If the intermediate test is passed, in the next exam session (January / February) it will be possible to take only a partial test relating to the last part of the course (5040%). The est will be composed by true/false questions, multiple choice answers, openended questions, explanations and short exercises for a total of about 2530 questions. The score assigned to each question/exercise depends on its difficulty. Erroneous answers to true/false questions will have a negative score. During the test, students may consult formulary and tables provided during the lessons. The calculator can be used for tests where calculating exercises are foreseen.
Learning outcomes
Knowledge and understanding: The student will be able to understand the statistical methodology for organizing and summarizing statistical data.
Applying knowledge and understanding: The student will be able to use statistical tools to draw conclusions from the data, formulate and solve simple problems of probability and statistical inference.
Making judgements: The student will be able to autonomous perform statistical analysis in various contexts.
Communication skills: The student will be able to interpret and expose the results correctly; furthermore he will be able to comment and explain the main statistical indices and the applications of the inferential method
Learning skills: Students will be able to learn new statistical concepts, indexes and tools.
Readings
Obbligatori:
Borra S., Di Ciaccio, A., Statistica: metodologie per le scienze economiche e sociali, McGrawHill, 2015.
Slide delle lezioni a cura del docente.
Altri testi consigliati:
Piccolo, D. (2010). Statistica per le decisioni: la conoscenza umana sostenuta dall'evidenza empirica, ilMulino.
Cicchitelli G., D’Urso P., Minozzo M. “Statistica: principi e metodi”, Edizioni Pearson, 2017.
Agresti A., Finlay B. Statistica per le scienze sociali. Pearson Italia.
Diamond I., Jefferies J. “Introduzione alla statistica per le scienze sociali”, McGrawHill.
Levine J., Szabat K. A., Stephan D.F. “Statistica” (7 Ed.) Pearson Italia.