Geoffrey Hubona, Ph.D.
Programming Statistical Applications in R is an introductory course teaching the basics of programming mathematical and statistical applications using the R language. The course makes extensive use of the Introduction to Scientific Programming and Simulation using R (spuRs) package from the Comprehensive R Archive Network (CRAN). The course is a scientific–programming foundations course and is a useful complement and precursor to the more simulation–application oriented R Programming for Simulation and Monte–Carlo Methods Udemy course. The two courses were originally developed as a two–course sequence (although they do share some exercises in common). Together, both courses provide a powerful set of unique and useful instruction about how to create your own mathematical and statistical functions and applications using R software.
Programming Statistical Applications in R is a “hands–on” course that comprehensively teaches fundamental R programming skills, concepts and techniques useful for developing statistical applications with R software. The course also uses dozens of “real–world” scientific function examples. It is not necessary for a student to be familiar with R, nor is it necessary to be knowledgeable about programming in general, to successfully complete this course. This course is ‘self–contained’ and includes all materials, slides, exercises (and solutions); in fact, everything that is seen in the course video lessons is included in zipped, downloadable materials files. The course is a great instructional resource for anyone interested in refining their skills and knowledge about statistical programming using the R language. It would be useful for practicing quantitative analysis professionals, and for undergraduate and graduate students seeking new job–related skills and/or skills applicable to the analysis of research data.
Instructor Details
Courses : 9
Specification: Programming Statistical Applications in R
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12 reviews for Programming Statistical Applications in R
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| Price | $12.99 |
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| Provider | |
| Duration | 11 hours |
| Year | 2020 |
| Level | All |
| Language | English |
| Certificate | Yes |
| Quizzes | No |
$12.99
Kevin Hampel –
This course is a nice introduction to programming statistical functions in R, which really focuses on hands on application of the material. Prof. Hubona explains the topics in a patient way. However the course has quiet an overlap with some other courses of Prof Hubona like the comprehensive programming course in R, which is a disadvantage, because if you take the other courses you will get quiet a lot repetitions in the lectures and exercises. Finally for some of the more advanced exercises there are no solution lectures.
Mitra Soleimani –
the most useful and detailed R online courses.
Scott MacNevin –
In depth, looks at a wide range of presentation options, vector functions, if else explained well, for and while loops explained well, useful practical examples to work through
Nicholas Marey –
When a new video starts, it appears that the lecturer started the new video significantly after where his previous video stopped. This makes it difficult to follow the instructor’s train of thought. Additionally, I could not find the problem list for the first section in the downloadable course content. Lecture 19 is a repeat of an earlier lecture about the use of a matrix in R.
Jonathan McBrien –
Finding the lecturer’s delivery quite stunted and somewhat rambling and I’m finding it all not very engaging. I hope that past General Discussion when (I expect) the course goes into the subject matter in more detail that the lecturer will hold my interest.
Nadjana St –
Good if you are looking to brush up on statistical programming, no experience in R required
Julian Ricardo –
Great framing of using R within greater context of comp sci, only slightly more disjointed at the end. Two thumbs up!!!
Jorge Enrique Ruiz L pez –
It’s a basic introduction, and the teacher did’t explained in detail how to install R and R Studio. I do not need that explanation, but there might be people who needs it.
Diogo Ribeiro –
To basic
Tony Meissner –
Doesn’t really explains things well and jumps around a bit. Some explanations appear not to be correct.
Daniel Rosales Casas –
Me parece un gran curso, retomando conceptos de estad stica optimizando al mismo tiempo las funcionalidades de R. El cual ya conoc a pero no a estos niveles. Quiza aplicaciones reales sea algo bueno, si no es mucho qu pedir. Con datos reales y actualizados en donde se plantea una hip tesis y se llega hasta la toma de decisiones. Quiz sea mucho pedir pero es lo que se me viene a la mente. Gran curso, saludos.
Fabian Scheidt –
The course is a short format of the comprehensive R programming course. It is good if you have not attended the former. Nevertheless, it adds valuable additions, because debugging is more elaborated. Also, the statistical programming aspect is highlighted, with the treatment of the Boostrap and the Jackknife. If you are interested, wait for a sale and crap for both courses.