This is a collection of data analysis & data modeling practices using R.

• General linear models practice

• Involved skills: data visualization,multiple regression, variable transformation, collinearity, ANOVA, tests of significance, model building strategies and interpretation

• Multivariate analysis practices

• Applying multivariate analyis on several datasets
• Invovled skills: data visualization, multiple regression, principal component analysis, discriminant analysis,factor analysis, cluster analysis, etc.

• dplyr package learning notes
  • dplyr is a R package for Data Manipulation
  • functions included: tbl_df(),filter(), select(), arrange(), mutate(), group_by() and summarise(), sample_n() and sample_frac(), and Chaining/Pipelining programming.
  • check the notes (in html): https://cdn.rawgit.com/yimihua2013/R-Programming-Practices/master/dplyr_notes/dplyr_notes.html