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Statistics One is designed to be a comprehensive yet friendly introduction to fundamental concepts in statistics. Comprehensive means that this course provides a solid foundation for students planning to pursue more advanced courses in statistics. Friendly means exactly that. The course assumes very little background knowledge in statistics and introduces new concepts with several fun and easy to understand examples. This course is, quite literally, for everyone. If you think you can't learn statistics, this course is for you. If you had a statistics course before but feel like you need a refresher, this course is for you. Even if you are a relatively advanced researcher or analyst, this course provides a foundation and a context that helps to put oneβs work into perspective. Statistics One also provides an introduction to the R programming language. All the examples and assignments will involve writing code in R and interpreting R output. R software is free! What this means is you can download R, take this course, and start programming in R after just a few lectures. That said, this course is not a comprehensive guide to R or to programming in general.
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
Data scientist's toolbox Project 1
The Leek group guide to data sharing
Plotting Assignment 1 for Exploratory Data Analysis
Repository for Programming Assignment 2 for R Programming on Coursera
Analytic projects developed in R
Interactive Maps from R
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JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
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Open source projects and samples from Microsoft.
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Data-Driven Documents codes.
China tencent open source team.