A Basic Course in Statistical Data Analysis Using R

We are pleased to announce the 3-day course "A Basic Course in Statistical Data Analysis Using R" on May 4 - 6, 2016 in Vancouver, British Columbia, Canada. This course is intended for novice R users who would like to learn how to perform statistical data analyses in R or for intermediate R users who would like to consolidate their understanding of how R operates. Both types of users will benefit from the review of statistical concepts covered during the course.

If you are interested in attending this course, would like to receive further details and be added to the list of participants, please e-mail the course instructor, Dr. Isabella Ghement, at isabella@ghement.ca or call her at 604-767-1250.

Alternatively, if you would like us to offer this course privately at your premises or provide you with information on our other course offerings, please let us know.

Course Topics

Day 1 of the course will cover data import/export, data summarization and data visualization with ggplot2.

Day 2 of the course will cover hypothesis testing, basic statistical analyses and automated reporting.

Day 3 of the course will cover data cleaning, data manipulation and basic elements of R programming.

Course Outline

On Day 1, we will discuss the following topics:

• Overview of R;
• Creating, commenting and saving R scripts;
• Importing standard data files (e.g., csv, txt, Excel) into R;
• Exporting data sets from R;
• Producing data summaries using the dplyr package;
• Understanding the philosophy behind the ggplot2 package for producing statistical graphs;
• Creating basic statistical graphs with ggplot2 (e.g., histograms, density plots, boxplots, scatter plots, time series plots);
• Creating advanced statistical graphs with ggplot2, which involve grouping and facetting;
• Customizing and annotating statistical graphs produced by ggplot2;
• Saving statistical grahs produced by ggplot2.

On Day 2, we will discuss the following topics:

• Statistical tests of hypotheses (e.g., t-test, chi-square test);
• One-Way Analysis of Variance;
• Simple and Multiple Linear Regression;
• Analysis of Covariance;
• Producing automated statistical reports using R Markdown.

On Day 3, we will discuss the following topics:

• Data cleaning (e.g., identifying erroneous values, detecting problems with the coding of variables, creating date variables);
• Data manipulation (e.g., creating new variables, subsetting the data, re-shaping the data);
• Data objects in R (e.g., vectors, factors, matrices, data frames, lists); <>
• Writing and using R functions;
• Writing "if else", "for" and "while" statements.

Benefits to Participants

By the end of the course, participants will have a working knowledge of R. In particular, participants will be able to:

• Organize their R workflow;
• Read data into R and export data from R using the rio package;
• Clean up and massage data using the tidyr, dplyr and magrittr packages;
• Work with dates using the lubridate package;
• Create elegant and insightful data visualizations with the ggplot2 package;
• Produce descriptive statistics (e.g., means, medians, standard deviations, interquartile ranges, correlations);
• Perform basic tests of hypotheses and interpret their output;
• Perform basic statistical analyses such as linear regression, one-way analysis of variance (ANOVA) and analysis of covariance (ANCOVA) and interpret their output;
• Write R functions and scripts for performing repetitive tasks;
• Produce simple automated reports which include tables, graphs and text using the intuitive R markdown language.

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;
• 30 days of free course-related technical support via e-mail 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 a basic knowledge of 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 installation will be distributed to participants approximately one week prior to the course.

Registration Form

The course registration form is available for download via the following links:

• Registration Form: WORD Document
• Registration Form: PDF Document

Registration

To register for this course, please complete and sign the above registration form and send it to us by e-mail at info@ghement.ca or fax it to us at 604-270-3922 by the registration deadline of April 18, 2016.

Location

Downtown Vancouver in the new British Columbia Institute of Technology (BCIT) Building, Room 830, 555 Seymour Street, Vancouver, British Columbia. (This course is not affiliated with BCIT.)

You can use the links below to plan your visit to the BCIT Downtown Campus:

• BC Translink (Public Bus, SkyTrain, Canada Line)
• Google Maps (Private Car)

View larger map

Dates and Times

Dates: May 4, 5 and 6, 2016 (Wednesday, Thursday and Friday)

Registration: On all days, course registration and set-up begin at 8:30am.

Time: The course starts at 9:00am and ends at 5:00pm on each day.

Cost

The attendance fee for the course is $885.00 plus 5% GST per participant and includes a bound copy of the Course Notes, a CD-ROM containing all course examples and exercises and 30 days of free course-related technical support following the course. The attendance fee also includes morning and afternoon coffee, tea and snacks.

Discounts

Groups of 3 or more participants from the same organization receive a 10% discount.

Cancellation Policy

• 100% refund if written notification of cancellation is received by April 11, 2016. Please note that no refunds will be issued after this date.
• In the event you become unable to attend after the April 11, 2016 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.

• The course is limited to 18 participants per day so we encourage you to register early. The registration deadline is April 18, 2016.
• 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 as soon as we receive your registration form.
• Please do not make any travel arrangements until your reservation has been confirmed by us in writing via e-mail. We will confirm your registration by April 20, 2016.