
Data Literacy
How to Make Your Experiments Robust and Reproducible
Description
Key Features
- Presents the content in an informal tone and with many examples taken from the daily routine at laboratories
- Can be used for self-studying or as an optional book for more technical courses
- Brings an interdisciplinary approach which may be applied across different areas of sciences
Readership
Bioinformaticians; biomedical and allied health sciences graduate students; graduate students and educated lay persons who are interested in handling data for research
Table of Contents
Part A: Experimental Design
1. “Most published findings are false!”
2. How to identify a promising research problem?
3. Experimental designs: measures, validity, randomization
4. Experimental design: Sampling, bias, hypotheses
5. Positive and negative controlsPart B: Getting a “feel” for your data
6. Refresher on basic concepts of probability and statistics
7. Data cleansing
8. Case studies of data cleansing
9. Hypothesis testing
10. The “new statistics”
11. ANOVA.
12. Nonparametric tests
13. Other statistical concepts you should knowPart C: Data Management
14. Recording and reporting experiments
15. Data sharing and re-use
16. Publishing
Product details
- No. of pages: 282
- Language: English
- Copyright: © Academic Press 2017
- Published: September 5, 2017
- Imprint: Academic Press
- Paperback ISBN: 9780128113066
- eBook ISBN: 9780128113073
About the Author
Neil Smalheiser
Affiliations and Expertise
Ratings and Reviews
Latest reviews
(Total rating for all reviews)
SriramPenumatcha Sun Sep 02 2018
Good
Good
Bawon T. Thu Jan 25 2018
one of my favourite book on data thinking
this book give me more insight behind and beyond data in sciences context