About this Course Note - This is an Archived course This is a past/archived course. At this time, you can only explore this course in a self-paced fashion. Certain features of this course may not be active, but many people enjoy watching the videos and working with the materials. Make sure to check for reruns of this course. Do you want to learn how to harvest health science data from the internet? Do you want to understand the world through data analysis? Start by exploring statistics with R! Skilled persons who can process and analyze data are in great demand today. In this course you will explore concepts in statistics that help you make sense out of data. You will learn the practical skills necessary to find, import, analyze and visualize data. We will take a look under the hood of statistics and equip you with broad tools for understanding statistical inference and statistical methods. You will also get to perform some really complicated calculations and visualizations, following in the footsteps of Karolinska Institutet’s researchers. You are probably reading this course description because you know that statistics and statistical programming are essential skills in our golden age of data abundance. Let’s say it again: Health science has become a field of big data, just like so many other fields of study. New techniques make it possible and affordable to generate massive data sets in biology. Researchers and clinicians can measure the activity for each of 30000 genes of a patient. They can read the complete genome sequence of a patient. Thanks to another trend of the decade, open access publishing, the results of such large scale health science are very often published for you to read free of charge. You can even access the raw data from open databases such as the gene expression database of the NCBI, National Center for Biotechnology Information. In this course you will learn the basics of R, a powerful open source statistical programming language. Why has R become the tool of choice in bioinformatics, the health sciences and many other fields? One reason is surely that it’s powerful and that you can download it for free right now. But more importantly, it’s supported by an active user community. In this course you will learn how to use peer reviewed packages for solving problems at the frontline of health science research. Commercial actors just can’t keep up implementing the latest algorithms and methods. When algorithms are first published, they are already implemented in R. Join us in a gold digging expedition. Explore statistics with R.
Sep 09, 2014
Days of the Week:
Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday
- Level of Difficulty: Beginner
- Size: Massive Open Online Course
- Instructors: Matilda Utbult, Mikael Huss, Peter Lönnerberg, Andreas Montelius
- Cost: Free
- Institution: EdX
- Topics: General Health, Statistics, Biology
EdX offers interactive online classes and MOOCs from the world’s best universities. Topics include biology, business, chemistry, computer science, economics, finance, electronics, engineering, food and nutrition, history, humanities, law, literature, math, medicine, music, philosophy, physics, science, statistics and more. EdX is a non-profit online initiative created by founding partners Harvard and MIT.
EdX Offers Courses In:
Mathematics, Health, Science