Think Stats
Allen Downey is a computer science associate professor at the Olin College of Engineering. He has taught computer science at Wellesley College, Colby College, and the University of California, Berkeley. He holds a Ph.D. in Computer Science from the University of California, Berkeley, as well as Master's and Bachelor's degrees from MIT.
If you know how to program, you can use probability and statistics tools to convert data into knowledge. This concise introduction demonstrates how to perform statistical analysis computationally, rather than mathematically, using Python programs.
You'll learn the entire process of exploratory data analysis by working with a single case study throughout Think Stats, from collecting data and generating statistics to identifying patterns and testing hypotheses. You'll learn about distributions, probability rules, visualization, and a variety of other tools and concepts.
Your discoveries will be enriched by new chapters on regression, time series analysis, survival analysis, and analytic methods.
- Write and test code to gain an understanding of probability and statistics.
- Experiment with statistical behavior by generating samples from various distributions.
- Use simulations to help you understand concepts that are difficult to grasp mathematically.
- Python can import data from most sources rather than relying on data that has been cleaned and formatted for statistics tools.
- Answer questions about real-world data using statistical inference.
Author: Allen B. Downey
Link to buy: https://www.amazon.com/Think-Stats-Exploratory-Data-Analysis/dp/1491907339
Ratings: 4.3 out of 5 stars (from 136 reviews)
Best Sellers Rank: #293,004 in Books
#119 in Data Modeling & Design (Books)
#330 in Python Programming
#410 in Probability & Statistics (Books)
