A Primer in Biological Data Analysis and Visualization Using R 2nd Edition by Gregg Hartvigsen ISBN 9780231202121 0231202121

Chapter 1. Introducing Our Software Team

1.1 Solving Problems with Excel (or Google Sheets) and R

1.2 Install R and RStudio

1.3 Getting Help with R

1.4 R as a Graphing Calculator

1.5 Using Script Files

1.6 Extensibility

1.7 Problems

Chapter 2. Getting Data into R

2.1 Using c() for Small Datasets

2.2 Reading Data from a Spreadsheet Program

2.3 Reading Data from a Website

2.4 Problems

Chapter 3. Working with Your Data

3.1 What Kinds of Data Are There?

3.2 Accuracy and Precision of Our Data

3.3 Gathering Data into Dataframes

3.4 Stacking Data

3.5 Subsetting a Dataframe

3.6 Sorting a Dataframe

3.7 Saving a Dataframe to a File

3.8 Problems

Chapter 4. Tell Me About My Data

4.1 What Are Data?

4.2 Where’s the Middle?

4.3 Dispersion About the Middle

4.4 Testing for Normality

4.5 Outliers

4.6 Dealing with Non-Normally Distributed Data

4.7 Problems

Chapter 5. Visualizing Your Data

5.1 Overview

5.2 Histograms

5.3 Boxplots

5.4 Barplots

5.5 Scatterplots

5.6 Bump Charts (Before and After Line Plots)

5.7 Pie Charts

5.8 Multiple Graphs (Using par() and pairs())

5.9 Problems

Chapter 6. An Overview of Science, Hypothesis Testing, Experimental Design, and Inference

6.1 What Do We Mean by the Term Statistics?

6.2 How to Ask and Answer Scientific Questions

6.3 The difference Between Hypothesis and Theory

6.4 A Few Experimental Design Principles

6.5 Using R to Assign Individuals to Treatments Randomly

6.6 Inference

6.7 How to Set Up a Simple Random Sample for an Experiment

6.8 Interpreting Results: What Is the p-value?

6.9 Type I and Type II Errors

6.10 Problems

Chapter 7. Hypothesis Tests: Using One- and Two-Sample Tests

7.1 One-Sample, Two-Tailed Test with Normally Distributed Data

7.2 One-Sample, One-Tailed Test with Normally Distributed Data

7.3 One-Sample Tests with Non-Normally Distributed Data

7.4 Paired Data That Are Normally Distributed

7.5 Paired Data That Are Not Normally Distributed

7.6 Tests with Two Independent Samples

7.7 Problems

Chapter 8. Hypothesis Tests: Differences Among Multiple Samples

8.1 One-Way ANOVA

8.2 Interpreting Results from a One-Way ANOVA

8.3 Visualizing a One-Way ANOVA

8.4 One-Way Test for Non-Parametric Data

8.5 Two-Way ANOVA

8.6 Interpreting the ANOVA Table

8.7 Visualizing the Results of a Two-Way ANOVA Test

8.8 Problems

Chapter 9. Hypothesis Tests: Linear Relationships

9.1 Correlation

9.2 Linear Regression

9.3 Another Example of Regression Analysis

9.4 Problems

Chapter 10. Hypothesis Tests: Observed and Expected Values

10.1 The χ2 Test

10.2 An Example with Warts

10.3 The Fisher Exact Test

10.4 Problems

Chapter 11. A Few More Advanced Procedures

11.1 Writing Your Own Function

11.2 Adding 95% Confidence Interval Lines for Linear Regression

11.3 Nonlinear Regression

11.4 An Introduction to Mathematical Modeling

11.5 Problems

Chapter 12. An Introduction to Computer Programming

12.1 What Is a Computer Program?

12.2 Introducing Algorithms

12.3 Combining Programming and Computer Output

12.4 Problems

Chapter 13. Final Thoughts

13.1 Where Do I Go from Here?

Appendix Solutions to Select Problems

Bibliography

Index