Intensive Bootcamp Training on R – Package For Data Analysis and Statistical Modeling
October 3 @ 9:00 am - October 5 @ 5:00 pm
EVENT PRESENTATION
This will be a 3-day hands-on workshop centered on the R software package. The training in data analytics and statistical modeling will equip participants with practical skills through direct experience and practice. Sample datasets and code will be provided to facilitate practical work and immerse participants in real-world contextual analysis. A dataset will be supplied by the trainer for use during the sessions. Group work will also be organized to engage participants in analyzing, interpreting, and making recommendations based on a real-life dataset related to a public health challenge. Group work manuscripts will be submitted, and corrections for the exercises will be provided and discussed with participants.
This training aims to provide participants with high-quality skills to master the R software package for data analysis and statistical modeling, particularly in the context of operational and implementation research related to malaria. We are confident that this workshop will advance the career development and capacity building of prospective trainees and significantly strengthen the technical and communication skills of early-career researchers interested in modeling.
DATE AND TIME
October 3rd to 5th, 2024, from 9:00 AM to 5:00 PM CAT.
VENUE
Blue Work, Rue Ceper, Yaoundé.
TARGET AUDIENCE
- University students
- Postdocs
- Researchers
- Healthcare practitioners
- NMCP (National Malaria Control Program)
- CBOs (Community-Based Organizations)
- Local NGOs
Note: Priority will be given to registered local chapter members.
PROGRAM
| Day 1 (hands-on) | Day 2 (hands on) | Day 3 (hands on) |
| Morning session
• General orientation and introduction to statistics • Vectors • Matrices • Dataframes Afternoon Session • Installing packages • setting working directory and Importing data into R (xls, csv etc) • Data visualization (base plots)
|
Morning session
• Data wrangling/data cleaning • Missing data • One sample t.test and Two sample t.test Afternoon session • One sample and two sample Test of proportion • Chi-square test • Odds ratio, and confidence interval • Pearson Correlation
Group project – exercise on real life data with propose engaging solutions from participants
|
Morning session
• Linear regression models (simple One way Anova • Two way Anova • and multiple) • Logistic regression model Afternoon session • Poisson regression model • Survival analysis • Non-parametric tests (Sign test, Wilcoxon Rank Test, KruskalWallis test, Friedman test)
Group project – exercise on real life data with propose engaging solutions from participants |