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**Probability in R. Discrete Random Variables**

MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2 Hours | Lec: 13 | 314 MB

*Genre: eLearning | Language: English*

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Infermath a mathematical theory of programming applications to provide a high level of understanding of quantitative fields

the course is designed for students of probability and statistics who would like to enrich your learning experience using statistical programs

Infermath a mathematical theory of programming applications to give a high level of understanding of quantitative fields

probability, R is the rate of one mathematical theory with application programming. A series of discrete random variables gives an overview of the most important distributions discrete probability and methods of their generation in the fundamental language features of R. R is introduced including logical conditions, loops, and descriptive statistics. The audience will be acquainted with basic knowledge of numerical analysis.

The course is designed for students of probability and statistics who wish to enrich their experience of statistical programming. Although a basic knowledge of probability theory and calculus is a useful condition that is not necessary. The proposed method of use of course, repeating the arguments and replication code R. Therefore, it is important for students to download and use R in.

The course consists of twelve short lectures totaling two hours of video. Four main themes: distribution Bernoulli (2 lectures), binomial distribution (3 lectures) geometric distribution (3 lectures) and the Borel-Cantelli Lemma (4 lectures). Eight lectures presented in the form of writing code R. the Remaining four lectures focus on the theory of probability.

As Infermath different from other channels of education? It equips students with the tools and skills to apply the acquired knowledge in practice. It aims to show that learning mathematics is not only useful but also fascinating and inspiring. It focuses on equal chances in education and promotes open approach.

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