Data Analysis
A.Y. 2022/2023
Learning objectives
Aim of the course is to gain a series of basic competences for retrieving, treating, analysing and presenting qualitative and quantitative information. More in detail, students will learn how to perform queries in digital catalogues, as well as in online datahubs with political, economic and juridical data, and how to download the relevant information in different formats. Furthermore, they will further learn how to use the most common electronic spreadsheets to catalogue, analyse and present those data.
Expected learning outcomes
After taking this course students should be familiar with the Unimi electronic databases, and will be able to download research articles and access datasets. They will know how to pose a (research) question and download relevant data published by international organization and institutes such as IMF, WB, OECD, WGI, Eurostat, Eurobarometer, etc. Finally, they will be able to describe and communicate findings of simple descriptive analyses using graphs and tables produced with Microsoft Excel.
Lesson period: First trimester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First trimester
Course syllabus
1) Introduction to data analysis with Excel
a. Organisation & logistics
b. Excel basics
2) Data, variables, and measurement level
3) How to describe a variable
4) Getting and importing data
5) Data management with Excel
6) Analysing data with Excel pivotTables
7) EXCEL Charts
8) Bivariate analysis I
a. Chi-squared test of independence
b. T-test for difference in means
9) Bivariate analysis II:
a. Correlation
b. Regression
10) How to effectively summarise and present your work.
a. Organisation & logistics
b. Excel basics
2) Data, variables, and measurement level
3) How to describe a variable
4) Getting and importing data
5) Data management with Excel
6) Analysing data with Excel pivotTables
7) EXCEL Charts
8) Bivariate analysis I
a. Chi-squared test of independence
b. T-test for difference in means
9) Bivariate analysis II:
a. Correlation
b. Regression
10) How to effectively summarise and present your work.
Prerequisites for admission
There are no preliminary requirements different from those requested for the registration to the bachelor's degree.
Teaching methods
Lectures held in classroom and streamed through Microsoft Teams based on weekly slides and handouts.
Laboratories will consist of registered Microsoft Excel tutorials shared on Ariel. Students will then have the opportunity to meet the course tutor online or in presence in small groups.
Course material (slides, labs, and data) will be made available on Ariel at the following address: https://fviscontida.ariel.ctu.unimi.it.
Laboratories will consist of registered Microsoft Excel tutorials shared on Ariel. Students will then have the opportunity to meet the course tutor online or in presence in small groups.
Course material (slides, labs, and data) will be made available on Ariel at the following address: https://fviscontida.ariel.ctu.unimi.it.
Teaching Resources
Slides and handouts provided by the instructor on Ariel and Microsoft Teams.
Assessment methods and Criteria
Attending students are assessed according to the following criteria:
Assignments: 75%
Group research project: 25%
The assessment for non-attending students relies on a computer-based exam lasting 70 minutes. The exam is divided in two parts. In the first, students will have to answer open-ended and yes-and-no questions on statistics and Microsoft Excel. In the second part, students will have to retrieve data and perform practical exercises using Microsoft Excel.
Assignments: 75%
Group research project: 25%
The assessment for non-attending students relies on a computer-based exam lasting 70 minutes. The exam is divided in two parts. In the first, students will have to answer open-ended and yes-and-no questions on statistics and Microsoft Excel. In the second part, students will have to retrieve data and perform practical exercises using Microsoft Excel.
INF/01 - INFORMATICS - University credits: 3
Basic computer skills: 20 hours
Professor:
Visconti Francesco
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