# 11 Asking for help

In this lesson we learn about how to ask for help in R. This is probably the most important skill to learn in R.

## 11.1 Help, Hilfe, Au Secours!

R is very (very!) complete as a statistical language. As such, it has many functions, and many ways to achieve wanted results. For this reason I believe one of the most important aspects of learning R is to know how to find help for your problem. There are several ways you can do this, from inside and outside RStudio and R.

R function | Description |
---|---|

?function | help about a specific function |

??function | search the Help System |

help(“R function”) | primary interface to the help system |

help.search(“R function”) | search the Help System |

library(help = “package name”) | opens R documentation |

apropos(“R function”) | list all functions containing string foo |

example(“R function”) | show an example of function foo |

help(datasetname) | open details on a sample dataset |

vignette(“package name”) | opens Vignette of R package |

vignette() | show all available vingettes |

browseVignettes() | list of vignettes from installed packages |

## 11.2 How to use a given technique in R for the first time

Sometimes you know what you want to do, say, fit a Item Response Theory model to your data, but you do not know how to start. In that case, **CRAN Task Views** is definately a place to start. It summarize R resources in particular areas of application, helping your to navigate the maze of thousands of R packages. There you find a list with general topics, for example, **Psychometrics** or **Social Sciences**, which contains all R packages, their functionality, and a brief explanation. The importance and utility of CRAN Task Views cannot be overestimated, and it is the first place I go in these circumstances.

## 11.3 Error messages

Sometimes you try to run a function and you receive an **error message**. If it is not immediatly understandable what the problem is from the message, it can be particularly helpful to paste an error message into a search engine to find out whether others have solved a problem that you encountered. In specific, I find particularly useful to use Google with “R” or “in R” and the name of an R package, function (or both). Say, for example, “How to summarize data per group in R”.

## 11.4 Asking for Help

If you find that you can’t answer a question or solve a problem yourself, you can ask others for help on the internet. For example, there is a **dedicated Chat room** for discussion of all things about and related to the R statistical programming language. There you can simply ask questions away. I know I have gotten pretty good answers back in last than 30s.

In case you have a statistical question, or a question that is not purely R-related, there are several other websites in which you can find help.

Website | Description |
---|---|

Cross Validated | Statistics, data analysis |

Stack Overflow | Data Science and Machine learning |

Data Science beta |
Data Science and Machine learning |

Bioconductor.org | Data Science focused on Bioinformatics |

Biostars.org | Bioinformatics-specific questions |

**Etiquette 1**: In order to ask a question effectively, it helps to phrase the question clearly, and, if you’re trying to solve a problem, to include a small, self-contained, reproducible example of the problem that others can execute. For information on how to ask questions, **see the R posting guide**, and the document about **how to create reproducible examples for R on Stack Overflow**.

**Etiquette 2**: Do not cross-post among any of these venues.

## 11.5 R Email Lists

The R Project maintains a number of *subscription-based email lists* for posing and answering questions about R, including the general R-help email list, the R-devel list for R code development, and R-package-devel list for developers of CRAN packages; lists for announcements about R and R packages; and a variety of more specialized lists. Before posing a question on one of these lists, please read the R mailing list instructions and the posting guide. Here’s the link.

## 11.6 R FAQs (Frequently Asked Questions)

There are three primary FAQ listings which are periodically updated to reflect very commonly asked questions by R users. There is a Main R FAQ, a Windows specific R FAQ and a Mac OS (OS X) specific R FAQ.