This 3-day workshop shows participants how to use ChatGPT for statistical analysis without having to use a statistics program or writing a single line of code. The seminar covers a range of topics from data preparation and descriptive statistics to regression analysis, advanced statistical tests, and data visualisation. Special emphasis is placed on understanding the workings and limits of AI models, on the choice of the appropriate [i]mode[/i] and model and on assessing the output. The course also reflects on implications of AI for data analysis and the academic research process more generally.

Topics Covered
Examples for the ChatGPT Advanced Data Analysis , Models and modes of ChatGPT , Main features of ChatGPT , Customizing ChatGPT , Alternatives to ChatGPT , Descriptive Statistics , Creating Tables , Dispersion and Correlation , How Advanced Data Analyics works , How ChatGPT works , The P.R.O.P.E.R framework from prompts , Promises and Limits of ChatGPT , Precision and context , Q&A session , Updates , Tools , Setting up local LLMs , How-to , The A2I framework , ChatGPT strategies , Privacy and local LLMs , How AI changes the statistics profession , Reproducable science with ChatGPT and Python , The Future of Colloquial Statistical Analysis , Extracting textual data , Statistical analysis of textual data , Visualizing textual data , Sentiment and content analysis , Preparing datasets for ChatGPT , Extracting data with ChatGPT , ChatGPT data formats , Cleaning data with ChatGPT , Using the right mode of ChatGPT , Understanding the context window , Visualizing distributions , Visualizing relations , Visualizing time series , Data maps , Interactively improving visualizations , Consistent visualizations , Regression analysis , Statistical language and statistical tribes , Verbal interpretation , Automated LaTeX reports