Using AI for Quantitative Data Analysis

Description:

Introduction/Overview

This course will show you how ‘off the shelf' AI tools like ChatGPT can make even complex data analysis tasks easier and more efficient. Whether you have some experience with data analysis but feel daunted by statistical software or coding, or you’re a seasoned analyst looking to streamline your workflow, this course will equip you with practical techniques to harness AI tools effectively and ethically.

We will focus particularly on how tools like ChatGPT can help you perform data analysis and create sophisticated visualisations in programming languages like R – without having to write code yourself. We will also learn how these tools can help us to interpret statistical tables and outputs, and take the ‘grunt work’ out of writing up our analyses.

Learning Outcomes

By the end of the workshop participants will:

• Have a good understanding of the basics of how AI tools like ChatGPT actually work (and why they sometimes make mistakes)
• Have a good understanding of the different ways in which AI tools can help researchers conduct quantitative data analysis
• Be able to use AI tools effectively to generate code to conduct statistical analyses in R, using natural language prompts
• Be able to use these tools to produce sophisticated data visualisations in R
• Be able to use AI tools to help interpret complex statistical tables and write up results, while being aware of their limitations for this purpose

Topics

During the course we will cover:

• Introduction to Large Language Models
• Introduction to applications of AI tools to quantitative data analysis, including: code generation, interpretation of results, report writing, and ‘whole analysis’ tools.
• Generating R code for statistical analysis with AI tools
• Generating R code for data visualisation with AI tools
• Using AI tools for the interpretation of statistical outputs (including checking for errors)
• Using AI tools to assist in quantitative report-writing

Who will benefit?

This course is intended primarily for two audiences:

1. Participants who have some experience of data analysis, but are hampered from conducting more sophisticated analyses (or creating more complex visualisations) because they lack experience with, or feel intimidated by, complicated statistical software or writing code.
2. Participants who have more experience with complex data analysis and statistical software, but who want to use AI tools to be more productive or make their workflow more efficient.

Course Tutor

Dr Robert de Vries is Senior Lecturer in Quantitative Sociology and Deputy Head of the School of Social Sciences at the University of Kent. His research explores on inequality and social mobility, with a strong commitment to conducting quantitative research with integrity – ensuring that the research conclusions are based on robust evidence. He is the author of Critical Statistics: Seeing Beyond the Headlines, an award-winning textbook that introduces essential statistical concepts through the lens of understanding the numbers that surround us in our everyday lives.

Cost:

£180 for SRA members, £235 for non-members

Website and registration:

Register for this course

Region:

International

Keywords:

Frameworks for Research and Research Designs, Data Collection, Data Quality and Data Management , Qualitative Data Handling and Data Analysis, Quantitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis, ICT and Software, Research Management and Impact, Research Skills, Communication and Dissemination, AI and machine learning

Related publications and presentations from our eprints archive:

Frameworks for Research and Research Designs
Data Collection
Data Quality and Data Management
Qualitative Data Handling and Data Analysis
Quantitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis
ICT and Software
Research Management and Impact
Research Skills, Communication and Dissemination
AI and machine learning

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