# Data Mining and R

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This post lists a few data mining resources in R. I also provide a few observations on the distinction between data mining, data analysis, and statistics as it pertains to the analysis work that I do in psychology.**Jeromy Anglim's Blog: Psychology and Statistics**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

**Online Resources**

- The classic book
*The Elements of Statistical Learning*by Hastie, Tibshirani, Friedman is available for free online. There’s also an accompanying R package. - I previously discussed David Mease’s online data mining course
- Rattle – a data mining GUI for R.
- Some comments on data mining by John Maindonald
- Luis Torgo has a book currently available online providing demonstrations of data mining using R
- Cran Task View on Machine Learning & Statistical Learning

**Some Casual Observations**

**Data mining seems more concerned with prediction using observed variables than with understanding the causal system of latent variables; psychology is typically more concerned with the causal system of latent variables.**- Data mining typically involves massive datasets (e.g. 10,000 + rows) collected for a purpose other than the purpose of the data mining. Psychological datasets are typically small (e.g., less than 1,000 or 100 rows) and collected explicitly to explore a research question.
- Psychological analysis typically involves testing specific models. Automated model development approaches tend not to be theoretically interesting.

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