Online Course by Harvard University – Statistics and R program
This course explain you some introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.
If you want to know what these two are, you can enroll for the free online course.
You will understand some basics statistical inference which is one of stepping stones for knowledge of some other program. You will be provided R programming examples in a way that will help make the connection between concepts and implementation. Problem sets requiring R programming will be used to test understanding and ability to implement basic data analyses. We will use visualization techniques to explore new data sets and determine the most appropriate approach. We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches. By using R scripts to analyze data, you will learn the basics of conducting reproducible research.
In order to make each student from different background learn best, the courses are divided the series into seven parts.
- PH525.1x: Statistics and R for the Life Sciences
- PH525.2x: Introduction to Linear Models and Matrix Algebra
- PH525.3x: Statistical Inference and Modeling for High-throughput Experiments
- PH525.4x: High-Dimensional Data Analysis
- PH525.5x: Introduction to Bioconductor: annotation and analysis of genomes and genomic assays
- PH525.6x: High-performance computing for reproducible genomics
- PH525.7x: Case studies in functional genomics
What are the main keys you will learn?
- Random variables
- Inference: p-values and confidence intervals
- Exploratory Data Analysis
- Non-parametric statistics