Data Literacy

Data Literacy: How to Make Your Experiments Robust and Reproducible provides an overview of basic concepts and skills in handling data, which are common to diverse areas of science. Readers will get a good grasp of the steps involved in carrying out a scientific study and will understand some of the factors that make a study robust and reproducible.The book covers several major modules such as experimental design, data cleansing and preparation, statistical analysis, data management, and reporting. No specialized knowledge of statistics or computer programming is needed to fully understand the concepts presented.

This book is a valuable source for biomedical and health sciences graduate students and
researchers, in general, who are interested in handling data to make their research reproducible
and more efficient.

• 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

Bioinformaticians; biomedical and allied health sciences graduate students; graduate students and educated lay persons who are interested in handling data for research

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 controls

Part 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 know

Part C: Data Management
14. Recording and reporting experiments
15. Data sharing and re-use
16. Publishing