Data Literacy: How to Make Your Experiments Robust and Reproducible

Author:   Neil Smalheiser (Associate Professor, Department of Psychiatry and Psychiatric Institute, University of Illinois School of Medicine, USA)
Publisher:   Elsevier Science Publishing Co Inc
ISBN:  

9780128113066


Pages:   282
Publication Date:   11 September 2017
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Data Literacy: How to Make Your Experiments Robust and Reproducible


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Author:   Neil Smalheiser (Associate Professor, Department of Psychiatry and Psychiatric Institute, University of Illinois School of Medicine, USA)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Weight:   0.590kg
ISBN:  

9780128113066


ISBN 10:   0128113065
Pages:   282
Publication Date:   11 September 2017
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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 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

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Dr. Neil Smalheiser has over 30 years of experience pursuing basic wet-lab research in neuroscience, most recently studying synaptic plasticity and the genomics of small RNAs. He has also directed multi-disciplinary, multi-institutional consortia dedicated to text mining and bioinformatics research, which have created new theoretical models, databases, open source software, and web-based services. Regardless of the subject matter, one common thread in his research is to link and synthesize different datasets, approaches and apparently disparate scientific problems to form new concepts and paradigms. Another common thread is to identify scientific frontier areas that have fundamental and strategic importance, yet are currently under-studied, particularly because they fall “between the cracks” of existing disciplines. This book is based on lecture notes that Dr. Smalheiser prepared for a course he created, “Data Literacy for Neuroscientists”, given to undergraduate and graduate students.

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