Unit Data Analysis for communication
- Course
- Public, digital and corporate communication
- Study-unit Code
- A001467
- Curriculum
- Comunicazione d'impresa
- Teacher
- Maria Giovanna Ranalli
- Teachers
-
- Maria Giovanna Ranalli
- Hours
- 63 ore - Maria Giovanna Ranalli
- CFU
- 9
- Course Regulation
- Coorte 2022
- Offered
- 2022/23
- Learning activities
- Caratterizzante
- Area
- Discipline della comunicazione pubblica e d'impresa
- Academic discipline
- SECS-S/01
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian. International and Erasmus students are invited to take the course. Readings and other course material are also available in English; written and/or oral exams, as detailed in the course program, may be taken in English. Please contact the instructor for further details and to schedule an appointment during the first week of the Spring Semester.
- Contents
- 1. How to get data (polls and sample surveys, sampling designs, sampling and non-sampling error, data quality)
2. Data Analysis: descriptive statistics, graphical tools, time series analysis.
3. Bivariate analysis: association, contingency tables, correlation and regression.
4. Statistical tools for evaluating public policies and communication campaigns. Potential outcomes. - Reference texts
- CORBETTA, La ricerca sociale: metodologie e tecniche. IV L'analisi dei dati, Il Mulino, Bologna, 2015.
A. MARTINI, M. SISTI, Valutare il successo delle politiche pubbliche, Metodi e casi, Il Mulino, Bologna, 2009.
Suggested for excel
Giuliani, Dickson, Analisi statistica con Excel, Maggioli editore, 2015. - Educational objectives
- Make the student aware of the role and function of data and of statistical and evaluation methods in modern societies; provide the knowledge base needed to interpret, critically evaluate, produce and, therefore, adequately communicate statistical data regarding social and economic phenomena. Provide students with the tools to find statistical data to meet the information needs of the company and / or of the public sector, to know how to critically contribute to the design of a survey or of a poll. Provide students with the tools to know how to critically assess the quality of data from surveys and polls, knowing how to analyze such data to extract the necessary information in the public domain or enterprise and, therefore, know how to build and communicate quantitative information. Make the students able to provide feedback based on quantitative evidence with a good level of autonomy, making them aware of the criticality and complexity of the process of evaluation of public policies and / or of communication campaigns.
- Prerequisites
- All the required technical tools of data analysis and statistics will be introduced in the course. The knowledge of some simple tools of mathematics, such as proportions, percentages and the Cartesian plane are useful prerequisites, although non essential, as well as the knowledge of the Excel software.
- Teaching methods
- Face-to-face lectures and computer lab sessions. The slides shown during the lectures along with practical cases analyzed and the data used in class and in the lab are made available on the website of the course.
- Other information
- See the course webpage at Unistudium
- Learning verification modality
- The evaluation mode differs between attending and non-attending students.
For students attending the course, there are two written tests (exemptions). The first one (after approximately 5 weeks) focuses on topics related to polls, statistical surveys and statistical tools for univariate analysis, while the second one (at the end of the course) focuses on statistical tools for bivariate analysis and evaluation of public policies and communication campaigns. The written exams are "closed book" tests and contain both theoretical questions and more technical exercises with examples of real-life data analysis or construction of a survey or a poll. The first type of questions aims at assessing the degree of knowledge of the methods and of the analysis tools, while the latter intends to evaluate the ability to choose and use these methodologies and tools to solve real-life problems. Each test exemption is passed with a score equal to or greater than 16. In view of the proposed activities in the computer lab for students attending the course, a set of four "homeworks" to be done with the software Excel are also an evaluation tool. The final score is constructed by combining the results achieved in these three sets of evaluation tools using the following weights: homeworks (20%), the first exemption (40%), the second exemption (40%). The oral test for those who achieve in this way a minimum score of 18 is optional. The oral exam consists of a discussion of the written tests to assess any problems or deficiencies found. If the student decides to take the oral test, the final score is a combination of the results obtained in all the tests using the following weights: homework (20%), the first exemption (35%), the second exemption (35%), oral examination (10%).
Students not attending the course have to undergo both a written and an oral exam. The written exam is "closed book" and contains both theoretical questions and exercises that are more technical with examples of real-life data analysis, evaluation or construction of a survey or a poll. The first type of questions aims at assessing the degree of knowledge of the methods and of the analysis tools, while the latter intend to evaluate the ability to choose and use these methodologies and tools to solve real-life problems. The written test is passed with a score equal to or greater than 16. The oral examination is compulsory and consists of a discussion of the written test to assess any problems or deficiencies found. The final score is a combination of the results obtained in the two tests using the following weights: written test (70%), oral examination (30%).
In case the health emergency will require hybrid teaching, the exemptions and the written test will be held on the online platform LibreEol. Oral examinations will be held online via Teams. - Extended program
- 1. How to get data. Polls and sample surveys.
The steps of a statistical survey, questionnaire design, interview mode, mixed mode surveys
Probabilistic sampling designs (simple random sampling, systematic, stratified, cluster sampling), nonprobabilistic sampling designs (quota sampling, snowball sampling)
Sampling error and sample size
Reweighting of data
Nonsampling error and data quality
2. Data analysis: univariate analysis tools
counts, relative frequencies, percentages, cumulative distribution
average values (mode, median, quantiles, arithmetic mean)
graphical representations
variability of distributions (interquartile range, indices based on deviations, variance)
simple time series analysis (index numbers, relative changes)
3. Data analysis: bivariate analysis tools
contingency tables, association indices linear regression and interpolation of a time series analysis of the correlation between two variables
4. Statistical tools for evaluating public policies and communication campaigns. Definition and measurement of the effect of a policy; result variable and treatment variable; potential outcomes; selection bias and experimental methods; spontaneous dynamic. Method of difference in differences; universal policies and the method of interrupted time series