Statistics Done Wrong
Alex Reinhart is a Carnegie Mellon University statistics instructor and Ph.D. candidate. He earned a BS in physics from the University of Texas at Austin and conducts research on radioactive device detection using statistics and physics.
Scientific progress is dependent on good research, which requires good statistics. But statistical analysis is difficult to master, even for the brightest among us. It's surprising how many scientists get it wrong.
Statistics Done Wrong is a concise, essential guide to statistical blunders in modern science that will teach you how to avoid making mistakes in your research. You'll look at embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these errors to occur, and start your journey to change the way you and your peers do statistics. The book is regarded as one of the best books on statistics.
You can get advice on:
- Asking the appropriate question, designing the appropriate experiment, selecting the appropriate statistical analysis, and sticking to the plan
- What are p values, significance, insignificance, confidence intervals, and regression?
- Selecting the appropriate sample size and avoiding false positives
- Reporting your findings and making your data and source code available
- Procedures to be followed, precautions to be taken, and analytical software that can assist
Author: Alex Reinhart
Link to buy: https://www.amazon.com/dp/1593276206
Ratings: 4.5 out of 5 stars (from 303 reviews)
Best Sellers Rank: #126,940 in Books
#43 in Business Statistics
#98 in Statistics (Books)
#164 in Probability & Statistics (Books)
