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Statistics for Bench Biologists Who Hate Math: A Field Guide, One Bench Scenario at a Time
Paperback
BiologyGeneral ScienceProbability & Statistics
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ISBN13: 9798175228893
Publisher: Independently Published
Published: Sep 18 2026
Pages: 154
Weight: 0.61
Height: 0.33 Width: 7.00 Depth: 10.00
Language: English
Publisher: Independently Published
Published: Sep 18 2026
Pages: 154
Weight: 0.61
Height: 0.33 Width: 7.00 Depth: 10.00
Language: English
Statistics does not have to feel like a second language. Statistics for Bench Biologists Who Hate Math translates the statistics experimental biologists use every day into plain language, real lab scenarios, and decisions you can actually make. Instead of starting with abstract formulas, this practical field guide starts with the questions bench scientists really face: What does n actually count? When should you use a t-test or ANOVA? What is pseudoreplication? What does a confidence interval really tell you? Inside, you will learn how to:
- understand what n really counts
- choose among t-tests, ANOVA, post-hoc tests, and nonparametric alternatives
- avoid pseudoreplication, p-hacking, and misleading graphs
- interpret p-values, confidence intervals, power, outliers, and multiple comparisons
- use GraphPad Prism and R more confidently
- report statistical results clearly in papers, protocols, and reviewer responses Built around 23 practical chapters, worked examples, figures, software workflows, and bench cheat sheets, this book is designed for graduate students, technicians, postdocs, principal investigators, and anyone who wants statistics to become a useful scientific tool rather than a wall of symbols. Better questions lead to better analysis - and better biology.
- choose among t-tests, ANOVA, post-hoc tests, and nonparametric alternatives
- avoid pseudoreplication, p-hacking, and misleading graphs
- interpret p-values, confidence intervals, power, outliers, and multiple comparisons
- use GraphPad Prism and R more confidently
- report statistical results clearly in papers, protocols, and reviewer responses Built around 23 practical chapters, worked examples, figures, software workflows, and bench cheat sheets, this book is designed for graduate students, technicians, postdocs, principal investigators, and anyone who wants statistics to become a useful scientific tool rather than a wall of symbols. Better questions lead to better analysis - and better biology.
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