Statistical computing is employed within a diverse range of industries. In recent years, an open source project, R, has emerged as the preeminent statistical computing platform. With its unsurpassed library of freely available packages, R is capable of addressing almost every statistical inference p
DurationStatistical computing is employed within a diverse range of industries. In recent years, an open source project, R, has emerged as the preeminent statistical computing platform. With its unsurpassed library of freely available packages, R is capable of addressing almost every statistical inference problem.
In this course, you will learn the most commonly-used (roughly 100) functions and operators from the R Base Package, which serves as the fundamental tools for accessing data from multiple sources, manipulating different types of R objects, performing character manipulation, and generating reports. Furthermore, you will also learn how to write your own functions by using different types of control structures.
At UC San Diego Division of Extended Studies, we believe great social and economic prosperity comes from integrating the collective knowledge of the university, community leaders and professionals. Division of Extended Studies strives to combine local impact with national reputation and global reach.
In this course, you’ll use advanced modeling techniques to predict, classify and group data. You’ll use more advanced techniques to help you understand both inferential and predictive approaches.
The R Programming Introduction course will help students learn how to perform data analysis with the R language and software environment, even if they have little to no programming experience.
The Certified Financial Analytics Practitioner' (CFAP) course is a focused 32-hour instructor-led training and certification program that equips participants to explore+analyze+solve financial sector problems using popular analytics tools such as R & Advanced Excel.
Accelebrate's Introduction to R Programming training course teaches attendees how to use R programming to explore data from a variety of sources by building inferential models and generating charts, graphs, and other data representations.
Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience.
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