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Course Description

Overview

Complex data require complex statistical analyses.  Data that are large, messy, multi-dimensional, and in unconventional formats often require advanced data science approaches for proper rigorous analysis.  This workshop will expand on participants' prior knowledge of basic R programming and statistics to teach advanced analyses, including statistical modeling, empirical statistical analyses, and basic machine learning.  In this interactive workshop, participants will first learn the theory underlying analyses, then watch demonstrations of running analyses in R, and finally practice running analyses themselves.  Note that prior knowledge of basic R and statistics are required to be successful in this workshop, such as completion of the BIOF098 workshop or the STAT101 course.

 

Objectives

Upon completing the workshop, attendees will have the confidence, knowledge, and resources to

  1. Understand and fit statistical models (ANOVA, regression)
  2. Perform model selection
  3. Run empirical statistical analyses (bootstrapping, simulations, imputation)
  4. Understand and fit basic machine learning models

 

Target Audience

Researchers with basic knowledge or R and statistics seeking to expand their skillsets and/or move toward data science-focused roles.

 

Prerequisites

Attendees should have basic knowledge of R and statistics to successfully complete this advanced workshop.  Prior completion of the BIOF098 workshop or the STAT101 course will provide adequate background.

 

Related Workshop
BIOF 097 | Practical Scientific Statistics

BIOF 098 | Introduction to Statistical Analysis in R

Credit
Although no grades are given for courses, each participant will receive Continuing Education Units (CEUs) based on the number of contact hours. One CEU is equal to ten contact hours. Upon completion of the course each participant will receive a certificate, showing completion of the workshop and 2.8 CEUs.

This workshop applies toward the Bioinformatics Curiosity digital badge.

Refund Policy
100% tuition refund for registrations cancelled 14 or more calendar days prior to the start of the workshop.

50% tuition refund for registrations cancelled between 4 to 13 calendar days prior to the start of the workshop.

No refund will be issued for registrations cancelled 3 calendar days or less prior to the start of the workshop.

Notification
All cancellations must be received in writing via email to Ms. Carline Coote at registrar@faes.org.

Cancellations received after 4:00 pm (ET) on business days or received on non-business days are time marked for the following business day.

All refund payments will be processed by the start of the initial workshop.

 

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To Register Click on "Add to Cart"

Section Title
Advanced Statistical Analysis using R
Type
Online Synchronous
Days
T, W, Th
Time
9:00AM to 5:00PM
Dates
Jan 25, 2022 to Jan 27, 2022
Schedule and Location
Contact Hours
24.0
Location
  • ONLINE
Fee (Includes Tuition and Technology Fee)
Eligible Discounts Can Be Applied at Checkout $1,250.00
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