The Ultimate Guide to Graphing and Statistics in R

Dr. Nigel Gale introduces graduate students to statistical analysis, hypothesis testing, and data visualization using R and RStudio.

Ecologists, environmental scientists, foresters, horticulturalists, and biologists have two specific requirements for performing statistical analyses. This video is a primer - a simple and hopefully straightforward distillation of the essential components amidst the vastness of the field. This was presented to graduate students in the Faculty of Forestry at the University of Toronto. Covering ANOVA, regressions, correlations, and constructing bar graphs and line plots. First is a general introduction to probability, inference assumptions, and hypothesis testing. The second requirement is to perform the analyses, including managing the data using some statistical software. At the vanguard of such software is the R statistical software r-project.org/; and its integrative environment Rstudio rstudio.com/. However, few programs constitute the virtues of open-sources highly integrated and powerful programs as the R statistical software - taught to the modern student in most institutions. The following video comprises the time-stamped functions and analyses: 1. Intro to data management, probability, and data presentation (0:00-13:00 min) 2. Intro to producing graphs with R studio (13:15 - 17:00 min) 3. Subsetting the data (23:20) 4. 'attach' function in R (23:47 min) 5. 'summary' (24:45 min) 6. Using the plot function (28:00 - 34:00 min) 7. Package 'sciplot' for bar graphs 'bar graph.CI' function (34:00 - 36:00 min) 8. Analysis of Variance including Tukey HSD (ANOVA) (36:00 - 40:00 min) 9. Creating Line Plots and Scatter plot ( 42:00-45:00 min) 10. Regression analyses via 'lm' function - linear - (45:00 - 48:00 mins) 11. Correlation analysis (48:00 -51:00 mins) The video finishes with a summation of what we've learned. If you like this material, then please like and subscribe to this channel.