A Short Course on Data Analysis Using R Software

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Registration Now Open!
Come & Join Us!
 
A Short Course on Data Analysis Using R Software
 
Date: 11-12 September 2017
Venue: USM@KL, Universiti Sains Malaysia, Aras 8 (Penthouse), Menara Wisma Sejarah, 230 Jalan Tun Razak, 50400 Kuala Lumpur.
 
About the course:
This is an applied course on data analysis. In the course, participants will acquire skills to manage, visualize and analyse data. In addition to that, they will learn to interpret and present statistical results following recommended guidelines.
The course will use R and RStudio software. The concept of confounding and interaction in the statistical modelling will also be briefly discussed.
The analysis focuses on General and Generalized Linear Models. However, statistical notation and formulae will be kept at minimum.
Speaker(s)
Assoc. Prof. Dr. Kamarul Imran Musa
Dr. Wan Nor Arifin Wan Mansor
 
Topic(s)
· Getting started with R
· Data management
· Reproducible report with Rmarkdown
· Exploratory Data Analysis
· Data Visualization
· General Linear Model
- Linear regression
· Generalized Linear Model
- Logistic regression
- Poisson regression
- Cox PH regression
· Guides on reporting statistical results
 
Who will benefit from the course:
Epidemiologists
Applied statisticians
Data analysts
Post-graduate students
Data scientists
Academicians
 
Registration Fee:
Professionals – RM550.00
Students – RM450.00
 
For more information, please contact
Mdm. Ham Siew Ling 
This email address is being protected from spambots. You need JavaScript enabled to view it.| 09-767 3801| 012 - 928 9664 (preferred WhatsApp)
 
Download Brochure : Page 1 | Page 2
 
 
 
Payment Term
 
Payment can be made by Online Transaction or Cash Deposit. only. 
 
Account Name : USAINS TECH SERVICES SDN. BHD.
Account Number : 8006815124
Bank Name : CIMB Bank
 
Please send transaction proof by WhatsApp to +6-012-9289664 / email : This email address is being protected from spambots. You need JavaScript enabled to view it.
For more information please call 09-767 3801

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