This is the code repository for Learn By Example: Statistics and Data Science in R Video, published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
This course is a gentle yet thorough introduction to Data Science, Statistics and R using real life examples. Let’s parse that. Gentle, yet thorough: This course does not require a prior quantitative or mathematics background. It starts by introducing basic concepts such as the mean, median etc. and eventually covers all aspects of an analytics (or) data science career from analyzing and preparing raw data to visualizing your findings. Data Science, Statistics and R: This course is an introduction to Data Science and Statistics using the R programming language. It covers both the theoretical aspects of Statistical concepts and the practical implementation using R. Real life examples: Every concept is explained with the help of examples, case studies and source code in R wherever necessary. The examples cover a wide array of topics and range from A/B testing in an Internet company context to the Capital Asset Pricing Model in a quant finance context.
- Harness R and R packages to read, process and visualize data
- Understand linear regression and use it confidently to build models
- Understand the intricacies of all the different data structures in R
- Use Linear regression in R to overcome the difficulties of LINEST() in Excel
- Draw inferences from data and support them using tests of significance
- Use descriptive statistics to perform a quick study of some data and present results
To fully benefit from the coverage included in this course, you will need:
This course has the following software requirements:
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