You've always wanted to analyze your research data!

Preparing the data, creating data summaries, modeling and much more!!


Here's an opportunity to learn how to do all of these in a systematic and organized way.
More importantly--doing it properly!!

Join online LIVE training on

STATISTICAL ANALYSIS WITH R FOR REPRODUCIBLE RESEARCH


A 30-hour course taught by
Enayetur Raheem, Ph.D.

What you will Learn



Applied Statistics

Learn enough statistics to understand statistical analyses found in scientific papers

R for Data Analysis

Learn tidyverse ecosystem of R for research data analysis with minimal coding

Reproducible Research

Create reproducible report with publication-quality tables and figures

Course Description



"Statistical Analysis with R for Reproducible Research" prepares biomedical, public health, and researchers in other fields to perform statistical analysis of research data. This course teaches statistical concepts essential for research and statistical analysis of data for scientific publications and reporting.

The reproducibility of research has become an essential requirement for many scientific journals and among the scientific community.

With powerful open-source R tools for statistical computing, you will learn how to project-manage your entire analytic workflow and carry out statistical analysis with the reproducibility of results built into it.

No prior R programming experience is required. But general computer literacy is needed either in Windows or Mac environments. 

To be successful in this course, you should be comfortable installing / uninstalling software, as well as using Windows Explorer or equivalent tools to find and organize files and folders.

Key Learning Outcomes



After completing the course requirements, you would

  • understand statistical analyses presented in biomedical, public health, and social science journal papers
  • perform statistical analysis and use appropriate hypothesis testing procedures to answer research questions  
  • be comfortable handling and analyzing data  
  • become familiar with R for data analysis 
  • be able to create reproducible statistical reports  
  • be able to create publication-ready tables and figures  
  • learn analytic project management for improved efficiency

Who this course is for



This course is most suitable for those actively working on a research project.

Or someone aiming to become an independent researcher in biomedical, public health, or other fields where statistical analysis is essential.

However, this course can benefit anyone interested provided that they are–

  • Highly motivated and self-disciplined individuals
  • Currently working or will potentially work on hypothesis-driven scientific research projects 
  • Active researchers and students who want to perform statistical analysis on their own 
  • Researchers without formal statistics training who wish to understand statistical analysis performed in published literature 
  • Researchers who need some refresher on statistics 
  • Students/researchers wishing to learn the tidyverse ecosystem of tools for data analysis 
  • Wishing to better manage their data analysis projects for efficiency and reproducibility 

Who this course is NOT for



This course is not for–


  • Those who want to learn research methodology. This course will not teach you research methodology
  • Researchers looking for Python-based data analysis training 
  • Learning how to build models for the sole purpose of predictions 
  • Not committed to allocating 6-8 hours per week for six to eight weeks 
  • Not disciplined to attend classes and complete the required activities (watching video lectures, homework assignments) on time 

About the Instructor



Enayetur Raheem, Ph.D.

is a statistician and educator. He is an accomplished data scientist with over 20 years of analytic experience in academia and US healthcare industry combined. He has taught graduate level statistics courses at Dhaka University and several universities in the US prior to transitioning to industry as a Data Scientist. He is a lifelong learner and passionate about teaching online.  He is the founder and principal instructor at dataskool.org -- an online analytic learning platform.


Course Fee Structure (Proposed)



Professionals

15,000 BDT / 150 USD

12,750 BDT / 125 USD
(15% off  Early registration before 1 Mar 2022)

BRF/ResearchWay Trainee

12,750 BDT / 125 USD

11,250 BDT / 110 USD
(25% off Early registration  before 1 Mar 2022)

Students (MS or under)

11,250 BDT / 110 USD

10,500 BDT / 105 USD
(30% off Early registration before 1 Mar 2022) 

Want to learn more about the course?
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