We will provide tips on where to find a statistician to join your research team and how to foster a productive, strong collaboration with them. Additionally, we will discuss two common challenges, determining appropriate authorship and the scope of working with EHR data.
Learn about when Python could be a better choice than a language such as R, as well as learn some of the basics of Python. No prior programming experience is needed.
Learn how to use SAS software for basic data management to prepare data for analysis. We will cover importing data from Excel and CSV formats, creating and editing variables, and dataset manipulations.
Come learn how to do simple statistics (including t-tests, Chi-square tests, correlations, and simple linear regression) using SAS. Prior programming experience in SAS is recommended (due to the one-hour time frame) but not required. Code and example data from the session will be made freely available to all attendees.
Learn how to use R to prepare data for analysis. We will cover data import and data cleaning. Prior programming experience in R is not required. Code and example data from the session will be made freely available to all attendees.
Join for a session on how to create figures in R using the ggplot2 package. Topics to be covered include proper formatting for your data, understanding ggplot syntax and grammar, creating simple figures such as bar charts and scatter plots, and exporting publication-quality figures. Prior experience using R is recommended, but not a prerequisite, and example code will be provided after the session.
Come learn how to do simple statistics (including t-tests, Chi-square tests, correlations, and simple linear regression) using R. Prior programming experience in R is recommended (due to the one-hour time frame) but not required. Code and example data from the session will be made freely available to all attendees.
