Think Stats: Exploratory Data Analysis, Edition 3
About this ebook
Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place.
- Analyze data distributions and visualize patterns using Python libraries
- Improve predictions and insights with regression models
- Dive into specialized topics like time series analysis and survival analysis
- Integrate statistical techniques and tools for validation, inference, and more
- Communicate findings with effective data visualization
- Troubleshoot common data analysis challenges
- Boost reproducibility and collaboration in data analysis projects with interactive notebooks
About the author
Allen B. Downey is a Professor of Computer Science at Olin College of Engineering. He has taught computer science at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Masterâs and Bachelorâs degrees from MIT. He is the author of Think Python, Think Bayes, Think DSP, and a blog, Probably Overthinking It.
