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Data Literacy
How to Make Your Experiments Robust and Reproducible
An overview of basic concepts and skills in handling data that is ideal for diverse areas of science
Neil Smalheiser (Author)
9780128113066
Paperback, published 11 September 2017
282 pages
23.4 x 19 x 1.9 cm, 0.59 kg
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 andresearchers, in general, who are interested in handling data to make their research reproducibleand more efficient.
Part A: Experimental Design1. “Most published findings are false!?2. How to identify a promising research problem?3. Experimental designs: measures, validity, randomization4. Experimental design: Sampling, bias, hypotheses5. Positive and negative controls Part B: Getting a “feel? for your data6. Refresher on basic concepts of probability and statistics7. Data cleansing8. Case studies of data cleansing9. Hypothesis testing10. The “new statistics?11. ANOVA. 12. Nonparametric tests13. Other statistical concepts you should know Part C: Data Management14. Recording and reporting experiments15. Data sharing and re-use16. Publishing
Subject Areas: Biomedical engineering [MQW], Clinical & internal medicine [MJ]
