Introduction to R and Statistics in the Life Sciences

Introduction to R and Rstudio

•Introduction to R Packages and Documentation.
• General introduction to R and its integrated development environment, RStudio. 
• Basic R Syntax: includes data types, variables, and basic operations.
•Students will learn how to load data into R, import data from various file formats (e.g., CSV, Excel), and perform simple data manipulations.

Data Visualization Packages and Techniques:

•Hands-on how to install these packages from CRAN or Bioconductor sources, for data visualization.
• Starting with very basic plotting functions in R to create simple visualizations like scatter plots, bar charts, and histograms.
• More advanced techniques with ggplot2, which offers customization options for creating high quality publication-quality plots.

Basic Statistics 

•Introducing summary statistics, hypothesis testing methods.
• Simple and multiple linear regression to understand the relationship between dependent and independent variables.
• Analysis of Variance (ANOVA) statistical technique for comparing means across multiple groups of experiments.  
•Clustering techniques

Hands-On Projects:

•Assign data visualization and analysis tasks on a given test dataset that is suitable for Engineering or Life Sciences students.  
•Encouraging to explore and solve problems independently under my support and guidance as required.