R for Researchers


 An introduction to R program and how to use it for beginners. The course is mainly designed to familiarize participants with the program before using it in a professional way for their research purpose.

Part 1:   What is R, reason to use it, packages for R, Installation, loading data and practicing.

Part 2:   Mathematical operations, Expressions, Logical values, Variables, Functions, Basic data types, Dealing with NA, and finding appropriate functionality.

Biostatistics with R: How to refine data before analyzing it, choose you appropriate test and interpret the data in a professional manner. This course is essential for all researchers for unbiased research analysis.

Basic graphics with R:  How to draw basic graphics using the base built in graphics package in R such as the line chart, bar chart, histogram, box and whiskers, combining graphics, and Scatter plot matrix.

Advanced graphics with R:  How to draw professional graphics for international publications and how to determine the appropriate graphics panel based data.

The course focuses on g plot 2 package, which is the  most powerful graphics package recommended by top leading journals such as Nature and Cell.

Correlation and Regression with R: Understand how to correlate variables and fit a regression model for data in a professional manner.

Logistic regression with R: Understand how to perform a logistic regression and predict binomial (binary) variable. Additionally, the course gives a hint on how to read and draw a logistic regression (S- shaped) curve.

Principle component analysis with R: A Multivariate analysis test used to predict strong correlation pattern within dataset variables. This course enables the user to perform, read and draw a PCA.

Receiver operating characteristics (ROC) curve with R: Understand how to perform and read a ROC curve. Choosing a cut point between poor and good observations.

Data manipulation with R: This course enables you to deal with large data input in a professional way. Unlike spreadsheet (excel), this tool enables you to avoid errors and save time by using automated coding.