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BioTech 98 | Statistical Analysis using R: Hands-on training

March 20, 2019 to March 22, 2019

Registration occurs on a first-come, first-served basis. The deadline for registration is one week before the first day of the course.  If you are unable to register before the deadline, please email: training@faes.org or call 301-496-7977 for space availability. 

NIH Only: Payment approval and authorization is done through your AO or lab manager. Receiving lab approval does not constitute enrollment. Fellows or those being sponsored by their lab can enroll using this form while waiting for authorization of payment.

Register Now

Contract: SF-182

Workshops generally run from 9:00am - 5:00pm.​

Background:
Data is everywhere. Every biologist has some kind of data. Data can be modelled, managed, transformed, analyzed, mined, explored and visualized using several different methods and tools. But, statistical methods are the most popular way to analyze data. And, R is the popular platform to perform statistical analysis.

Objectives:
This Hands-on training will help participants to learn to perform basic statistical analysis using the R platform. First, participants will learn to use the R and RStudio software platforms. Then, with a short introduction to basic statistical concepts, participants will do hands-on exercises to perform basic statistical analysis using the R platform.

Who should attend:

  • Clinicians, Researchers and Academics who have data to manage, clean, analyze, visualize and explore.
  • Program administrators who are interested in getting a firsthand experience working with the popular R platform for data analysis.

Hands-on Skills/Tools taught:

  1. Introduction to R, RStudio
    1. Data Types in R
    2. Data import
    3. Variables
    4. Operators
    5. Looping
    6. Functions
    7. Scripts
    8. Basic plots
  2. Statistical analysis using R
    1. Distributions
    2. Measures of central tendency
    3. Measures of variability
    4. Correlation
    5. Regression
    6. Statistical inference

Highlights:

  • Cloud-based, high performance computing platform
  • Training provided by active NIH researchers
  • Cookbook style bound manual for all exercises
  • Direct, after training support through exclusive forum membership
  • Continuing Education Credits

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