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Data storytelling

General data

Course ID:	2600-DSt-OG
Erasmus code / ISCED:	(unknown) / (unknown)
Course title:	Data storytelling
Name in Polish:	Data storytelling
Organizational unit:	Faculty of Management
Course groups:	General university courses General University Courses in Faculty of Management General university courses in the social sciences On-line general university courses
ECTS credit allocation (and other scores):	3.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	Polish
Type of course:	general courses
Prerequisites (description):	Online (via Zoom + Kampus)
Mode:	Remote learning
Short description:	The main goal of the course is to recognize the story behind the data and gain skills necessary to tell such a story. During the semester, students will analyze data and report the outcome in graphical form.
Full description:	During the course theoretical parts will be combined with practical training. This way participants will use theoretical knowledge in practice right away and will be able detect and understand story behind data and effectively present data in visual form. Students will work on their projects in small teams. Theoretical aspects of the course: 1. Data storytelling, data finding, statistical study 2. Basics of descriptive statistics 3. Basic of hypothesis testing 4. Data visualization Practice: 1. Exploratory data analysis using Excel 2. Visualization using Knightlab and Inforgram 3. Report building
Bibliography:	A. D. Aczel; Complete Business Statistics Cole Nussbaumer Knaflic; Storytelling danych. Poradnik wizualizacji danych dla profesjonalistów H. Rosling; Factfulness: Ten Reasons We're Wrong About the World--and Why Things Are Better Than You Think
Learning outcomes:	K_U02 – The student is able to correctly interpret technological, social, political, legal, economic and ecological processes and phenomena and their impact on the functioning of the organization and the entire economy, using the appropriate selection of computational methods. K_K01 – The student is ready to assess and critically approach situations and phenomena related to the functioning of the organization, sector and the entire economy using mathematical models.
Assessment methods and assessment criteria:	During the semester, students write two colloquia consisting of open computational tasks; To pass, it is required to obtain at least 60% of points in each test

Classes in period "Summer semester 2023/24" (in progress)

Time span:	2024-02-19 - 2024-06-16	Selected timetable range: weekly course term Navigate to timetable MO TU KON W TH FR
Type of class:	Seminar, 30 hours more information
Coordinators:	Bartłomiej Michałowicz
Group instructors:	Bartłomiej Michałowicz
Students list:	(inaccessible to you)
Examination:	Course - Grading Seminar - Grading
Notes:	(in Polish) Kurs skierowany jest dla studentów wszystkich Wydziałów UW z wyjątkiem: - Wydziału Zarządzania Zajęcia odbywają się w rytmie tygodniowym od 23.02 do 8.06. Spotkania synchroniczne odbędą się w dniach: 21.02 21.03 25.04 16.05 6.06 (wtorki) w godzinach 16.00-17.30 na ZOOM

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