Data storytelling 2600-DSt-OG
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
Course coordinators
Type of course
Mode
Prerequisites (description)
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 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
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
Notes
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Term 2023L:
None |