Elegant statistical graphics with R and ggplot2 - May 29 and 30, 2014

We are pleased to announce the hands-on course "Elegant statistical graphics with R and ggplot2" on Thursday and Friday, May 29 and 30, 2014. On both days, the course will take place between 8:30am and 5:00pm at the British Columbia Institute of Technology (BCIT), 555 Seymour Street, Vancouver, B.C., Canada. (This workshop is not affiliated with BCIT.) This course is ideal for participants who are relatively new to R as well as R users who wish to expand their proficiency in R by creating informative statistical graphics.

What is R?

R is a free, open-source software package with extensive statistical computing and graphics capabilities, which can be used to explore and analyze data. In addition to providing a comprehensive suite of conventional statistical tools, R has many freely available add-in packages which can be used to carry out more specialized statistical tasks. More information on R can be found on the website www.r-project.org. A user-friendly interface to R can be downloaded from www.rstudio.org.

Course Description

The open-source statistical software package R comes equipped with several packages for producing elegant graphics, and ggplot2 is one of the most powerful and versatile of these packages. This two-day course will provide participants with an in-depth introduction to ggplot2 in the context of graphics production for exploratory and confirmatory data analyses. Participants will learn how to use ggplot2 to produce, customize, and export publication-quality graphics that facilitate the communication of data-driven insights. In particular, participants will gain an understanding of the ggplot2 philosophy, syntax, and capabilities; learn how to create standard and advanced statistical graphs; and become skilled at customizing graphs through the addition of labels, titles, symbols, colors, legends, scales, annotations, layers, and themes. Participants also will learn how to combine the presentation of numerical and visual data summaries in the same graph, save ggplot2 output in a variety of standard graphical formats, and embed this output in automated reports and presentations. Modern principles for constructing informative statistical graphs will be discussed throughout the course. This hands-on course will offer participants the opportunity to practice the use of ggplot2 in real time. Participants are required to have basic knowledge of R and statistics and to bring their laptops pre-installed with R, R Studio and ggplot2 to the course.

Examples of Plots Produced with R and ggplot2

Benefits to Participants

After attending this course, participants will be able to:

• Understand the ggplot2 philosophy, general capabilities and syntax;
• Deconstruct a plot produced by ggplot2 into its basic components or layers;
• Work with various ggplot2 layers (e.g., data layer, geom layer, stat layer, general layer) and understand their respective functionality;
• Combine ggplot2 layers using the "+" notation in order to produce a variety of standard and advanced statistical graphs;
• Recognize variations in the ggplot2 syntax in order to be able to adopt and modify template ggplot2 code produced by other people;
• Build on ggplot2's grouping and faceting capabilities in order to slice the data into natural groups and reveal patterns that may be at play within each group;
• Enhance the default appearance of statistical graphs produced by ggplot2 through the addition of labels, titles, symbols, colors, legends, scales, annotations, layers, and themes;
• Present results produced by various types of statistical models (e.g., linear regression models, generalized linear regression models, generalized additive models, mixed effects models, time series models) using capabilities specific to ggplot2;
• Superimpose numerical and visual data summaries in the same statistical graph;
• Embed tables and plots inside other plots using the annotation facilities of ggplot2;
• Include plots produced by ggplot2 inside R functions using appropriate variable scoping rules;
• Save graphical output produced by ggplot2 in a variety of standard graphical formats (e.g., pdf, jpeg, png);
• Insert graphical output produced by ggplot2 in automated reports and presentations.
• Use modern principles of statistical graphics to create elegant and informative statistical graphs.

Course Outline

Day 1

• Overview of R Studio (e.g., installation, menus, workflow)
• Basics of ggplot2 (e.g., philosophy, capabilities, syntax fundamentals)
• Producing standard statistical graphs with ggplot2 (e.g., histogram, density plots, boxplots, scatterplots, time series plots, line plots, bar charts)
• Producing more elaborate statistical graphs with ggplot2 (e.g., scatterplot matrices, single-panel plots obtained via data grouping, multi-panel plots obtained via data faceting)
• Customizing graphs constructed with ggplot2 through the addition of labels, titles, symbols, colors, legends, scales, text annotations, layers and themes

Day 2

• Present results produced by various types of statistical models (e.g., linear models, generalized linear models, mixed effects models, time series models) using ggplot2 capabilities
• Incorporate data summaries, numerical tables and plots into graphs produced by ggplot2
• Embed plots produced by ggplot2 inside R functions using appropriate variable scoping rules
• Save graphical output produced by ggplot2 in a variety of standard graphical formats (e.g., pdf, jpeg, png)
• Embed graphical output produced by ggplot2 in automated reports and presentations

Course Format

This course is limited to 18 participants and consists of a series of short lectures and demonstrations followed by hands-on, interactive sessions for the participants. Each participant will be provided with:

• A bound copy of the Course Notes;
• A CD-ROM containing all examples and exercises used during the course;
• A variety of handouts on plot construction using R and ggplot2;
• 30 days of free course-related technical support following the course.

Course Leader

The course is led by Dr. Isabella Ghement. Isabella obtained her Ph.D. in Statistics from the University of British Columbia (UBC) in 2005. Isabella has presented numerous public and private workshops/courses on the statistical software package R to researchers, graduate students, government agencies and corporations in Canada. She also lectured part-time on advanced statistics at the Sauder School of Business, UBC between 2005 and 2012. Isabella is actively engaged in statistical consulting through her company Ghement Statistical Consulting Company Ltd. Her statistical consulting clients include federal and provincial government agencies, contract research organizations and academic researchers. Isabella co-authored the following publications based on her Ph.D. work on nonparametric regression: "Seasonal Confounding and Residual Correlation in Analyses of Health Effects of Air Pollution" (Environmetrics. 2007; 18(4): 375-394) and "Robust estimation of error scale in nonparametric regression models" (Journal of Statistical Planning and Inference. 2008; 138(10): 3200-3216). Most recently, Isabella has acquired statistical expertise in the field of mixed treatment comparisons, a generalization of meta-analytic methods allowing for the comparison of multiple medical interventions with respect to their efficacy and safety. In this field, Isabella has co-authored publications such as "Incorporating multiple interventions in meta-analysis: an evaluation of the mixed treatment comparison with the adjusted indirect comparison" (Trials 2009, 10:86 doi:10.1186/1745-6215-10-86), "Estimating the Power of Indirect Comparisons: A Simulation Study" (PLoS ONE 6(1): e16237. doi:10.1371/journal.pone.0016237) and "Multiple treatment comparison meta-analyses: a step forward into complexity" (Clinical Epidemiology. 2011; 3: 193-202).

Prerequisites

Participants should have some basic knowledge of R and statistics.

Participants should bring a laptop computer pre-installed with the open-source R software and its user-friendly interface R Studio.

R can be installed from http://cran.stat.sfu.ca and R Studio can be installed from http://www.rstudio.org.

In addition to R and R Studio, participants will be required to install several R packages on their laptops. Instructions on R package download will be distributed to participants approximately one week prior to the course.

Upon request, we can provide a computer for participants to use during the workshop for an additional cost of $100.00 plus HST per participant per day.

Location

Downtown Vancouver in the new British Columbia Institute of Technology (BCIT) Building, Room 820, 555 Seymour Street, Vancouver, B.C.
(Workshop not affiliated with BCIT)

Dates and Times

Dates: May 29 and 30, 2014.

Registration: On both days, course registration begins at 8:30 a.m.

Times: The course starts at 9:00 a.m. and ends at 5:00 p.m. on each day.

Cost

The attendance fee for this course is $265.00 per day plus 5% GST per participant (for a total of $556.50) and includes a bound copy of the Course Notes, a CD-ROM containing all course examples and exercises, a variety of course-related handouts, and 30 days of free course-related technical support following the course. The attendance fee also includes morning and afternoon coffee, tea and snacks.

If you would like us to provide a computer for you to use during the course please add $100.00 plus 5% GST per participant per day.

Discounts

• Groups of 2-5 participants from the same organization receive a 10% discount.
• Groups of 6 or more participants from the same organization receive a 15% discount.

Cancellation Policy

• 100% refund if written notification of cancellation is received by May 16, 2014. Please note that no refunds will be issued after this date.
• In the event you become unable to attend after the May 16, 2014 refund deadline, you may delegate a substitute attendee. Please notify us of any changes as soon as possible via e-mail at info@ghement.ca or telephone at 604-767-1250 or fax at 604-270-3922.

Registration

• The course is limited to 18 participants per day so we encourage you to register early. The registration deadline is May 20, 2014.
• To reserve your place, please follow the instructions below:
  
  1) Pre-register by e-mailing us at info@ghement.ca, or telephone us at 604-767-1250, or fax us at 604-270-3922.
  
  2) Complete the Registration Form.
  
  3) E-mail or fax the completed Registration Form to us, and mail your cheque payable to Ghement Statistical Consulting Company Ltd.; or request us to invoice your organization where indicated on the Registration Form.
  
  
• Your reservation will be confirmed via e-mail by May 22, 2014.
• Please do not make any travel arrangements until your reservation has been confirmed by us in writing via e-mail.

Registration Form

Please click here to download the registration form. For additional attendees, please duplicate the registration form.