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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)
  • TAF: Basic compulsory subjects SSD: SECS-S/01 CFU: 6
Teachers: Stefano GHINOI
Exam type written
Evaluation final vote
Teaching language Italiano
Contents download pdf download

Teachers

Stefano GHINOI

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

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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 corresponding to approximately 50-60% of the program. If the intermediate test is passed, in the next exam session it will be possible to take only a partial test relating to the last part of the course (50-40%). The test will be composed by true/false questions, multiple choice answers, open-ended questions, explanations and short exercises for a total of about 25-30 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, McGraw-Hill, 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”, McGraw-Hill.
Levine J., Szabat K. A., Stephan D.F. “Statistica” (7 Ed.) Pearson Italia.