tsaomao / edx--msds-curriculum--dat204x

Personal lab files for DAT204x course at edX as part of the Microsoft Data Science curriculum.

Further Readings for Chapter 1. Basics: To learn more about R's history and recent developments, you can visit www.r-project.org; it's the basis of the entire R community. Here, you will find guidelines to get started with R on your own local system. Next, you can head over to RStudio (http://www.rstudio.com/), to install an Integrated Development Environment (IDE) to work with R. Writing your own scripts, developing packages and using version control are made easy with this software.

For a structured overview of the basic data types that are used in R, you can visit R Tutorial (http://www.r-tutor.com/r-introduction/basic-data-types) to learn more about different elementary concepts.

Further Readings for Chapter 2. Vectors: Still want to know more about vectors? Well as a first aid, you can always consult the biggest library there is for R: r-project. In order to immediatly arrive at the right chapter click on the following link: r-project/vectors. (https://cran.r-project.org/doc/manuals/R-intro.html#Simple-manipulations-numbers-and-vectors)

As a second option you can again consult R-tutorial (http://www.r-tutor.com/r-introduction/vector), where you will find some more examples on vectors.

Further Readings for Chapter 3. Matrices: Need to know more about matrices in R? Don't worry, there is plenty of information available! The following webpage r-project/matrices (https://cran.r-project.org/doc/manuals/R-intro.html#Arrays-and-matrices) will guide you to the right piece of information inside the big library of r-project. Note that it also contains more advanced operations on matrices, like how to take the determinant of a matrix in R or how to transpose a matrix.

As an alternative source you can visit this webpage: ats.ucla.edu/matrices (http://www.ats.ucla.edu/stat/r/library/matrix_alg.htm) on the site of the Institute for Digital Research and Education. Here the concept of working with matrices in R is once again explained and some more technical examples are also discussed.

Further Readings for Chapter 4. Factors: Factors are handy right? Of course you want to know more! As always a good source is r-project, following this link r-project/factors (https://cran.r-project.org/doc/manuals/R-intro.html#Factors), you immediatly get to the right information.

The Swiss Federal Institute of technology in Zurich, also has some very good documentation on factors in R. You can find it on their website by following this link: stat.ethz.chse/factors (https://stat.ethz.ch/R-manual/R-devel/library/base/html/factor.html).

Further Readings for Chapter 5. Lists: Do you feel like you need to know even more about lists? No problem, r-project is again there for you. This link: r-project.org/Lists (https://cran.r-project.org/doc/manuals/R-intro.html#Lists), will guide you to the info you were looking for.

For more examples about lists, you can consult R tutorial, go to the examples by visiting this page on R tutorial (http://www.r-tutor.com/r-introduction/list).

Further Readings for Chapter 6. Data frames: Still aren't satisfied about your knowledge of dataframes? There are again some sources you can consult to go even deeper into the material. Yet again as a first aid you can consult r-project. By clicking this link r-project.org/Data-frames (https://cran.r-project.org/doc/manuals/R-intro.html#Data-frames), you will immediatly go to the right chapter.

You can also check out this page on R-tutorial (http://www.r-tutor.com/r-introduction/data-frame) if you want some extra examples and more information on data frames.

Further Readings for Chapter 7. Graphics: You are now familiar with the basics of plotting in R. Congratulations! Still hungry for knowledge? Visit this page on r-project (https://cran.r-project.org/doc/manuals/R-intro.html#The-plot_0028_0029-function) to learn even more about plotting in R.

As an alternative source, you could also have a look at statmethods/graphs (http://www.statmethods.net/advgraphs/axes.html). Here you can find some very well documented information about making plots in R.