14493 - AI-Assisted Statistics: Exploring Data with ChatGPT & Co Modulübersicht
| Module Number: | 14493 |
| Module Title: | AI-Assisted Statistics: Exploring Data with ChatGPT & Co |
| KI-unterstützte Statistik: Datenanalyse mit ChatGPT & Co | |
| Department: | Faculty 5 - Business, Law and Social Sciences |
| Responsible Staff Member: |
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| Language of Teaching / Examination: | English |
| Duration: | 1 semester |
| Frequency of Offer: | Every summer semester |
| Credits: | 6 |
| Learning Outcome: | After completing the course, students will be able to apply statistical concepts and methods to analyze real-world data effectively. They have the skills needed to conduct a simple empirical research project from start to finish, including defining a research question, collecting and analyzing secondary data, and presenting their findings. By integrating AI tools such as ChatGPT throughout the research process, students know how to enhance their efficiency and creativity in the process of hypothesis development, data analysis, and data interpretation. The course will also foster critical thinking, enabling students to reflect on the opportunities and limitations of using AI in research, as well as the ethical implications. Furthermore, students will develop their ability to communicate research findings effectively in both academic and non-academic contexts while improving their collaboration and problem-solving skills in team-based environments. |
| Contents: | The course Statistics with ChatGPT & Co. introduces students to the principles and practices of using AI-driven tools specifically gneeral purpose large language models (LLM), such as ChatGPT in the context of data analysis. IN groups, students will explore the research process, starting with identifying a research question and locating suitable secondary data sources online or in databases. The course provides hands-on training in statistical analysis, including descriptive statistics, regression techniques, and data visualization, with the aid of AI tools like ChatGPT to support each phase. Students will engage in reflective discussions about their experiences with AI in research, examining both its potential and its limitations. The centerpiece of the course is the development and execution of an independent research project, where students will collect, analyze, and interpret secondary data to address their chosen research question. Group work of up to thre epeople is possible. Alongside these activities, the course emphasizes the ethical and practical challenges of using AI in research, culminating in the presentation of findings in written and oral formats. |
| Recommended Prerequisites: | Basics in statistics, in particular simple regression analyses |
| Mandatory Prerequisites: | None |
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| Module Examination: | Continuous Assessment (MCA) |
| Assessment Mode for Module Examination: |
The presentation and the progress and reflection reports are done in working groups if projects have been worked on in working groups, for the term paper individual papers are handed in and graded individually - however, overlaps in the texts of members of the same group are allowed when group members are declared on the title page of the term paper. Groups are up to 3 members. |
| Evaluation of Module Examination: | Performance Verification – graded |
| Limited Number of Participants: | 30 |
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| Remarks: | None |
| Module Components: | Seminar |
| Components to be offered in the Current Semester: |