An accessible learning resource that develops data analysis skills for natural science students in an efficient style using the R programming language
R-ticulate: A Beginner’s Guide to Data Analysis for Natural Scientists is a compact, example-based, and user-friendly statistics textbook without unnecessary frills, but instead filled with engaging, relatable examples, practical tips, online exercises, resources, and references to extensions, all on a level that follows contemporary curricula taught in large parts of the world.
The content structure is unique in the sense that statistical skills are introduced at the same time as software (programming) skills in R. This is by far the best way of teaching from the authors’ experience.
Readers of this introductory text will find: - Explanations of statistical concepts in simple, easy-to-understand language - A variety of approaches to problem solving using both base R and tidyverse - Boxes dedicated to specific topics and margin text that summarizes key points - A clearly outlined schedule organized into 12 chapters corresponding to the 12 semester weeks of most universities
While at its core a traditional printed book, R-ticulate: A Beginner’s Guide to Data Analysis for Natural Scientists comes with a wealth of online teaching material, making it an ideal and efficient reference for students who wish to gain a thorough understanding of the subject, as well as for instructors teaching related courses.
R-ticulate: A Beginner’s Guide to Data Analysis for Natural Scientists is a compact, example-based, and user-friendly statistics textbook without unnecessary frills, but instead filled with engaging, relatable examples, practical tips, online exercises, resources, and references to extensions, all on a level that follows contemporary curricula taught in large parts of the world.
The content structure is unique in the sense that statistical skills are introduced at the same time as software (programming) skills in R. This is by far the best way of teaching from the authors’ experience.
Readers of this introductory text will find: - Explanations of statistical concepts in simple, easy-to-understand language - A variety of approaches to problem solving using both base R and tidyverse - Boxes dedicated to specific topics and margin text that summarizes key points - A clearly outlined schedule organized into 12 chapters corresponding to the 12 semester weeks of most universities
While at its core a traditional printed book, R-ticulate: A Beginner’s Guide to Data Analysis for Natural Scientists comes with a wealth of online teaching material, making it an ideal and efficient reference for students who wish to gain a thorough understanding of the subject, as well as for instructors teaching related courses.
Table of Contents
Preface
1 Hypotheses, Variables, Data
2 Measuring Variation
3 Distributions and Probabilities
4 Replication and Randomisation
5 Two-Sample and One-Sample Tests
6 Communicating Quantitative Information Using Visuals
7 Working with Categorical Data
8 Working with Continuous Data
9 Linear Regression
10 One or More Categorical Predictors - Analysis of Variance
11 Analysis of Covariance (ANCOVA)
12 Some of What Lies Ahead
