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Data Analysis for the Life Sciences with R

"Data Analysis for the Life Sciences with R" is published by Taylor & Francis Group in 2017 - Boca Raton, it has 1 pages and the language of the book is English.


“Data Analysis for the Life Sciences with R” Metadata:

  • Title: ➤  Data Analysis for the Life Sciences with R
  • Authors:
  • Language: English
  • Number of Pages: 1
  • Publisher: Taylor & Francis Group
  • Publish Date:
  • Publish Location: Boca Raton

“Data Analysis for the Life Sciences with R” Subjects and Themes:

Edition Specifications:

  • Weight: 0.455

Edition Identifiers:

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"Data Analysis for the Life Sciences with R" Description:

Open Data:

Cover -- Half Title -- Title Page -- Copyright Page -- Contents -- List of Figures -- Acknowledgments -- Introduction -- 1. Getting Started -- 1.1. Installing R -- 1.2. Installing RStudio -- 1.3. Learn R Basics -- 1.4. Installing Packages -- 1.5. Importing Data into R -- 1.6. Exercises -- 1.7. Brief Introduction to dplyr -- 1.8. Exercises -- 1.9. Mathematical Notation -- 2. Inference -- 2.1. Introduction -- 2.2. Random Variables -- 2.3. The Null Hypothesis -- 2.4. Distributions -- 2.5. Probability Distribution -- 2.6. Normal Distribution -- 2.7. Exercises -- 2.8. Populations, Samples and Estimates -- 2.9. Exercises -- 2.10. Central Limit Theorem and t-distribution -- 2.11. Exercises -- 2.12. Central Limit Theorem in Practice -- 2.13. Exercises -- 2.14. t-tests in Practice -- 2.15. The t-distribution in Practice -- 2.16. Confidence Intervals -- 2.17. Power Calculations -- 2.18. Exercises -- 2.19. Monte Carlo Simulation -- 2.20. Parametric Simulations for the Observations -- 2.21. Exercises -- 2.22 Permutation Tests -- 2.23. Exercises -- 2.24. Association Tests -- 2.25. Exercises -- 3. Exploratory Data Analysis -- 3.1. Quantile Quantile Plots -- 3.2. Boxplots -- 3.3. Scatterplots and Correlation -- 3.4. Stratification -- 3.5. Bivariate Normal Distribution -- 3.6. Plots to Avoid -- 3.7. Misunderstanding Correlation (Advanced) -- 3.8. Exercises -- 3.9. Robust Summaries -- 3.10. Wilcoxon Rank Sum Test -- 3.11. Exercises -- 4. Matrix Algebra -- 4.1. Motivating Examples -- 4.2. Exercises -- 4.3. Matrix Notation -- 4.4. Solving Systems of Equations -- 4.5. Vectors, Matrices, and Scalars -- 4.6. Exercises -- 4.7. Matrix Operations -- 4.8. Exercises -- 4.9. Examples -- 4.10. Exercises -- 5. Linear Models -- 5.1. Exercises -- 5.2. The Design Matrix -- 5.3. Exercises -- 5.4. The Mathematics Behind lm() -- 5.5. Exercises -- 5.6. Standard Errors

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