Essential Statistics for Bioscientists Front Cover

Essential Statistics for Bioscientists

  • Length: 256 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2022-07-25
  • ISBN-10: 1119712009
  • ISBN-13: 9781119712008
  • Sales Rank: #0 (See Top 100 Books)
Description

Dive into the most common statistical tests and software packages used for scientific data analysis and interpretation

In Essential Statistics For Bioscientists, experienced university and bioscientist Dr Mohammed Meah delivers  easy access to statistical analysis and data presentation. It is a great resource for students in the field of life and health sciences to conceptualize, analyze, and present data. This book uses three popular and commonly used statistics softwares―Microsoft Excel, Graphpad Prism, and SPSS―and offers clear, step-by-step instructions for essential data analysis and graphical/tabular display of data.

Beginning with fundamental statistics terminology and concepts, including data types, descriptive statistics (central and spread of data), exploratory statistics (graphical display) and inferential statistics (hypothesis testing and correlation), the content gradually builds in complexity, explaining which statistical test is best suited and how to perform it.

  • A thorough introduction to basic statistical terms and building up to an advanced level of statistical application- ideal for those new to study of statistics
  • Extensive application of three popular software packages- Microsoft Excel, Graphpad Prism and SPSS
  • Numerous hands-on examples of performing data analysis using Microsoft Excel, Graphpad Prism, and SPSS
  • Considers the limitations and errors of statistical analysis
  • Essential reading for those designing and planning a research project in Biosciences

Perfect for undergraduate students in the life and health sciences, Essential Statistics For Bioscientists will also earn a place in the libraries of anyone studying medicine, nursing, physiotherapy, pharmacy, and dentistry requiring a refresher or primer on statistical fundamentals.

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