Research and Data Analysis
These are outside resources that are available for students, but NMU does not directly endorse these. Consult your professors as to what academic resources you should use for your individual courses. Some resources may require payment or only be partially free.
AI can significantly enhance how you approach research and analyze data, making complex tasks more manageable and efficient. Whether you're sifting through academic papers, conducting surveys, or analyzing datasets, these tools can help streamline your process and deliver valuable insights.
1. Literature Review and Academic Research
AI tools make finding and organizing academic resources faster:
- Academic Paper Search:
- Semantic Scholar uses AI to highlight key concepts, citations, and related papers, helping you quickly identify relevant research.
- Connected Papers maps connections between papers to give you a visual overview of related work in your field.
- Citation Management:
2. Data Cleaning and Preprocessing
AI tools simplify messy datasets:
- Data Cleaning Tools:
- OpenRefine uses AI to clean and transform large datasets for analysis. It’s particularly useful for detecting and correcting inconsistencies.
- Trifacta Wrangler leverages AI to suggest data transformations and uncover patterns during preprocessing.
- Excel Add-Ins:
- Tools like Excel’s Analyze Data use AI to generate insights and suggest how to structure and clean your dataset.
3. Statistical Analysis
AI-powered software can simplify advanced statistical methods:
- Statistical Tools:
- No-Code AI for Data Analysis:
- RapidMiner provides drag-and-drop workflows for conducting statistical analysis without extensive coding knowledge.
4. Survey and Feedback Analysis
AI can streamline surveys and interpret results:
- Survey Tools:
- Google Forms provides basic AI features like auto-summarization of response patterns.
- Sentiment Analysis:
- Tools like MonkeyLearn use AI to analyze qualitative feedback and detect sentiment in open-text survey responses.
5. Programming and Machine Learning
For advanced research, AI tools can help you code and analyze:
- Code Assistance:
- GitHub Copilot offers coding suggestions and explanations as you work on data-related projects in Python, R, or other languages.