Covers algorithms of cleaning and munging data, probability theory and common distributions, statistical simulation, drawing inferences from data, and basic statistical modeling.
As an aspiring data scientist, it's important to know the foundations of probability and combinatorics, as these areas form the backbone of many concepts in data science. In the following lessons and ...
Introduction to Probability: it is a measurement of uncertainty. In this topic chances of the happening of events are considered. It is an experiment which if conducted repeatedly under homogeneous ...
This is an attractive textbook for an introductory probability course at the upper undergraduate level. It covers not only the standard material for such a course (discrete probability, the axioms of ...
Pishro-Nik's: Introduction to Probability, Statistics and Random Processes is a very ... and have made my Jupyter notebook for this chapter available here. Link to PDF of book.
This course provides an introduction to basic probability concepts. Our emphasis is on applications in science and engineering, with the goal of enhancing modeling and analysis skills for a variety of ...
Find out more about available formats and browse any associated online resources. This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical ...
This course provides an introduction to probability models including sample spaces, mutually exclusive and independent events, conditional probability and Bayes' Theorem. The named distributions ...
Introduction to probability, random processes and basic statistical methods to address the random nature of signals and systems that engineers analyze, characterize and apply in their designs. It ...