Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You’d be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free.

**Description**

You’ll find advice on:

- Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan
- How to think about p values, significance, insignificance, confidence intervals, and regression
- Choosing the right sample size and avoiding false positives
- Reporting your analysis and publishing your data and source code
- Procedures to follow, precautions to take, and analytical software that can help

**Table of Contents**

- Introduction
- An introduction to data analysis
- Statistical power and underpowered statistics
- Pseudoreplication: choose your data wisely
- The p value and the base rate fallacy
- When differences in significance aren’t significant differences
- Stopping rules and regression to the mean
- Researcher freedom: good vibrations?
- Everybody makes mistakes
- Hiding the data
- What have we wrought?
- What can be done?
- Conclusion

**Book Details**

Author(s): Alex Reinhart

Publisher: No Starch Press

Format(s): HTML(Online)

File size: –

Number of pages: 176

Link: Read online.

Publisher: No Starch Press

Format(s): HTML(Online)

File size: –

Number of pages: 176

Link: Read online.