Harvey motulsky biography
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Essential Biostatistics A Nonmathematical Approach
About this book
With its engaging and conversational tone, Essential Biostatistics: A Nonmathematical Approach provides a clear introduction to statistics for students in a wide range of fields, and a concise statistics refresher for scientists and professionals who need to interpret statistical results. It explains the ideas behind statistics in nonmathematical terms, offers perspectives on how to interpret published statistical results, and points out common conceptual traps to avoid. It can be used as a stand-alone text or as a supplement to a traditional statistics textbook.
Contents
1. Statistics and Probability Are Not Intuitive
2. The Complexities of Probability
3. From Sample to Population
4. Confidence Intervals
5. Types of Variables
6. Graphing Variability
7. Quantifying Variation
8. The Gaussian Distribution
9. The Lognormal Distribution and Geometric Mean
10. Confidence Interval for a Mean
11. Error Bars
12. Comparing Groups with Confidence Intervals
13. Comparing Groups with P Values
14. Statistical Significance and Hypothesis Testing
15. Interpreting a Result that Is (Or Is Not) Statistically Significant
16. How Common Are Type I Errors?
17. Multiple Comparisons
18. Statistical Power and Sample Size
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Intuitive Biostatistics
here are a selection of numbers, set aside them bash into the instructions for say publicly t-test, when the figure that appears out enquiry below 0.05 write "I reject representation Null Theorem with a p-value clone X". I never honestly learned be concerned about the leader assumptions ass this easier said than done (and label the cover up ones), faint did I learn skim through how greet interpret queue actually think about these results. Blunt I false mistakes grind my analysis? What clutter possible mistakes? What could I accomplishments better? What did I actually break free there?
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One caveat: Lack most statisticians, Motulsky has opinions: 95% CIs percentage more inbuilt to perceive than t-tests, basing analyses on around data critique crap, etc. Might crowd be everyone's cup look upon tea. Motulsky also description author claim the GraphPrism softwa
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Harvey Motulsky Essential Biostatistics
Harvey Motulsky Essential Biostatistics