In a previous article I provided a list of R programming resources. As a complement to that post, I’ve compiled a list of statistically oriented websites that colleagues and I have found useful below. For the most part, these sites focus on statistics and quantitative research methods rather than programming.

This first grouping lists sites that are mostly one-stop-shops for research design and analytical information. The first two, (and especially the UCLA website) are Tier I statistics/research methods sites. They are indispensable. The three remaining sites in this section cover less advanced topics and focus more on basics, but may be helpful for the R user who is more programmer than statistician.

The second group of sites is comprised of technical references such as statistical dictionaries and notation guides. The final section list two sites that have detailed information and examples focused on running statistical analyses in R. Note that the UCLA site also includes many examples using R.

### Comprehensive coverage

Statistical computing at UCLA

Statnotes: Topics in Multivariate Analysis, by G. David Garson

Introductory Statistics: Concepts, models, and applications

Social Research Methods Knowledge Base

Wolfram MathWorld

### Technical References

StatSoft statistical glossary

Glossary of technical notation

Dictionary of Algorithms and Data Structures

### R specific sites

Journal of Statistical Software

QuickR

If you know of another site for either R programming or statistics that I’ve missed, mention it in the comments below and I’ll add it to the proper list.

1. angggirobort says:

Statical references provides comprehensive details on statistics and quantitative research methods.Wonderful addition to this post regarding the best reference to get sufficent knowledge on this programming.I have boomarked youe dedicated site.

2. gelianwatosn says:

For acquiring wide variety of approaches and also helpful tricks,We have to choose perfect reference that will provide us useful  statistics resources and your recommendation towards statistical analysis is really an excellent post.Definitely i would love to follow your mentioned references.

3. ayush says:

Statistics and quantitative research provides a precise and well defined reports which is easy to understand and study.  I have gone through your previous post on r programming and now its complimentary is equally exiting too. Just hope they blend well together.

Thanks a lot for giving a list of references as supplement which can be followed to get a better idea on the concept. Looking forward to get more such useful posts.

4. saurabh says:

Thanks for posting. As a matter of fact, statistics and quantitative research provides a precise and well defined reports which is easy to understand and study.  I have gone through your previous post on r programming and now its complimentary is equally exiting too. Just hope they blend well together.

Thanks a lot for giving a list of references as supplement which can be followed to get a better idea on the concept. Looking forward to get more such useful posts.

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