Online Program

1003.0
Data visualizations: How to communicate evidence effectively--Fee: $300

Saturday, October 31, 2015: 9:00 a.m. - 5:00 p.m.
LI Course
Oral
Statement of Purpose and Institute Overview: The purpose of this course is to provide hands-on experience with the R programming language for computing basic statistics for data visualization like tables and graphs. Data visualizations are an effective way to communicate complex information about data to the audience (work-related or literature publication). However, without proper presentations, the information (data) can be misinterpreted, or ignored. Thus, it is imperative that the quality of the graphs, figures and tables submitted to and published in scientific journals has sufficient rigor so that it strengthens the overall manuscript. This course will teach participants how to use R (programming language), perform basic statistical procedures in R and learn about different ways to visualize data. Examples will focus on basic computing procedures used for exploratory analyses (tables and figures) including but not limited to: data import/export, summarizing data, calculating descriptive statistics, and plotting techniques for distribution, comparison and relationship figures and charts. This course will also provide several good and bad examples of graphs/tables appearing in manuscripts/presentations. This workshop combines a lecture and interactive discussion format. The lecture will provide background information on the importance of data visualization and how data visualizations are used to communicate in an effective way. While the interactive discussion is intended to use hands-on examples to gain a deeper understanding of the material taught in the lectures.
Session Objectives: Describe the importance of data visualization. Demonstrate how to effectively display public health data visually using R. Discuss some appropriate “dos and don’ts” for effective use of tables/charts/graphs/figures in scientific manuscripts or poster presentations.
Organizer:

9:00am
Introductory Remarks
9:15am
Getting Started: How to use R   
Kristina Dill, M.S.
10:00am
How to Use R, part II   
Kristina Dill, M.S.
10:30am
Break 15 minute break
10:45am
Summarizing Data   
Kristina Dill, M.S.
11:45am
Discussion An open discussion on the topics covered in the previous sections.
12:30pm
Lunch Lunch Break
1:30pm
2:30pm
3:30pm
Afternoon Break
3:45pm
Discussion An open discussion on the topics covered in the previous sections.
4:45pm
Concluding Remarks

See individual abstracts for presenting author's disclosure statement and author's information.

Organized by: APHA-Learning Institute (APHA-LI)

CE Credits: Medical (CME), Health Education (CHES), Nursing (CNE), Public Health (CPH) , Masters Certified Health Education Specialist (MCHES)