R for Quantitative Chemistry
eBook - ePub

R for Quantitative Chemistry

  1. 112 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

R for Quantitative Chemistry

About this book

R for Quantitative Chemistry is an exploration of how the R language can be applied to a wide variety of problems in what is typically termed "Quantitative Chemistry" or sometimes "Analytical Chemistry". Topics include: basic statistics, spectroscopic data, acid base equilibria and titrations, binding curves (of great current interest for biomedical applications), Fourier Transforms, and chemical kinetics and enzyme kinetics. An innovative feature is the discussion (as an alternative to the less stable nls packages) of the simplex adaptation subplex (R package) coupled with Monte Carlo analysis to determine confidence intervals for estimated parameters resulting from least squares optimization. Chemists who are interested in learning R as a research tool as well as Chemists who are teaching Quantitative Chemistry, as well as their students will be interested. This book is useful as most R books approach data analysis from an economic, social, medical, or biological context. Analysis of chemical data draws upon specific numerical models and a different set R programming and packages than is typically discussed in other disciplines. This book will be based upon, in large part, actual experimental data and will include end of chapter questions and projects. Readers are encouraged to email the author at [email protected] and to follow the accompanying blog on Medium "R Programming for Quantitative Chemistry".

Key Features:



  • Elements of R programming for Chemists


  • Literature Based Examples


  • Includes Binding Assay Analysis


  • Integrates theory, experiment, and R programming

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Yes, you can access R for Quantitative Chemistry by David K. Gosser in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Preface
  7. Author
  8. 1 Intro to R
  9. 2 Data and Statistics
  10. 3 Beer’s Law and Linear Regression
  11. 4 Solving Equilibrium
  12. 5 Titrations
  13. 6 Binding Curves
  14. 7 Electrochemistry
  15. 8 Fourier Transform and Spectroscopy
  16. 9 R Kinetic Analysis
  17. 10 Reports in R Markdown
  18. Index