data analysis r

Learn how to tackle data analysis problems using the powerful open source language R. The course will take you from learning the basics of R to using it to explore many different types of data. You will learn how to prepare data for analysis, compute various statistical measures, create meaningful data visualizations, create reusable R functions, create R models to predict expected future outcomes, and more! Course Syllabus Introduction to R Getting Started - R Console Data types and Structures Exploring and Visualizing Data Programming Structures, Functions, and Data Relationships General Information This course is free. It is self-paced. It can be taken at any time. It can be taken as many times as you wish. Labs can be performed on the Cloud, or using a 64-bit system. If using a 64-bit system, you can install the required software (Linux-only), or use the supplied VMWare image. More details are provided in the course. Students passing the course (by passing the final exam) will have immediate access to printing their online certificate of achievement. Your name in the certificate will appear exactly as entered in your profile in BigDataUniversity.com. If you did not pass the course, you can take it again at any time. Pre-requisites Recommended skills prior to taking this course Basic knowledge of statistics and any other programming language such as Python or Java is beneficial but not required. Grading Scheme The minimum passing mark for the course is 60%, where the final test is worth 100% of the course mark. You have 3 attempts to take the test. Enroll Now Browse more courses.
Part 1 in a in-depth hands-on series of videos introducing the viewer to Data Science using R. The video series illustrates the complete Data Mining project.
This page describes how to access and use the book Using R for Data Analysis and Graphics - Introduction, Examples and Commentary. Obtaining the Book Obtaining the data files You can reproduce the examples from the book by obtaining the data files from within R. You can get the data files by typing the following command from within R load(url( )) After typing this, you can use the ls() command to see what has been loaded. ls() [1] ais anesthetic austpop Cars93.summary dewpoint [6] dolphins elasticband florida hills huron [11] islandcities kiwishade last.warning leafshape milk [16] moths oddbooks orings possum primates [21] rainforest seedrates tinting If you wish to save the data on your computer, you can use the save.image() command. For example. save.image( myfile.rdata ) Suppose you then quit R and come back to R, you could then load the data with the load() command. load( myfile.rdata ) And you can see that you have loaded the data with the ls() command. ls() [1] ais anesthetic austpop Cars93.summary dewpoint [6] dolphins ishade last.warning leafshape milk [16] moths oddbooks orings possum primates [21] rainforest seedrates tinting How to cite this page Report an error on this page or leave a comment The content of this web site should not be construed as an endorsement of any particular web site, book, or software product by the University of California.