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73 changes: 73 additions & 0 deletions FAQ.md
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# Can we use the SAS university edition for workshops? #

We are looking into that. But probably!

# I have a Mac, can I use SAS? #

With the SAS University Edition you can. We personally have not tried
it, but it does say it can work for Mac's.

# How do I install SAS on a laptop without a CD drive? #

If you bought the SAS CD, it comes with a License key that you can use
to download SAS using the SAS Download Manager.

# Message `sh.exe: nano: command not found`. Help? #

> I was just practicing what we’ve done last Tuesday and I am getting
> this message for nano command: sh.exe”: nano: command not found. It
> worked well in class, but is not working now. Would you happen to know
> the solution? I did specify at the beginning git config --global
> core.editor "notepad"
Thanks for your question. Looks like your git was configured to use
Notepad as the text editor, not Nano. Try replacing "nano" with
"notepad" in your code and see if that works.

# What is a repository? #

> What exactly a repository is? Is it that folder we created named
> “practice”?
A repository is a history of all your commits. Everytime you do `git
commit`, it saves the files you are committing into the
repository. The physical repository is the `.git` folder, but it
tracks everything in that folder (the "practice" folder).

# Why do we need to check the repo's status so often? #

Checking often is important to make sure you are aware of what is
going on in your repository.

# What exactly the "untracked" means? #

"Untracked" means that the file is seen by git, but is not
followed. So any changes to the file will not be recognized by git
*until* you follow it (track it). (Like following people on Facebook
or twitter. They exist when you aren't following them, but you don't
keep updated on their status or what they are doing.).

# What happens with the saved files but not committed? #

Saved files (`git add` you mean?) are put into the staging area so
that they can be committed into the history (the git repository). If
you don't commit them, they stay there, but they do *not* go into the
history. Modified files (when you *don't* `git add` them, continue to
stay modified as you edit them, but they do not get saved until you do
`git add` and `git commit`.

# 'No new line at the end of file' after running `git diff` #

This can easily be fixed by pressing Enter at the bottom of the file.
This occurs because (more or less) Git follows the Unix convention.
If you want a more detailed answer, see
[this answer on the why](http://stackoverflow.com/a/5813359/2632184)
and
[this answer on the history of why](http://stackoverflow.com/questions/729692/why-should-files-end-with-a-newline).

# My terminal is stuck and I can't get back to the prompt (`$` or `>`) #

If you ever get stuck in the terminal, hit `Control-c` to 'c'ancel the
command and get back to the prompt (the `$` or `>` characters).


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26 changes: 26 additions & 0 deletions README.md
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Code As Manuscript Workshops
============================

This series of *hands-on* workshops aims to introduce students to the
concept of research reproducibility and to get the students practicing
with using version control systems and with using modern techniques in
R (or SAS) that make analyses less error prone and reproducible, and
that make you more efficient, productive, and in control. Techniques
for using version control systems to faciliate greater collaboration
among peers are also taught. The ultimate goal of the workshop is to
show how to reduce the number of steps needed to go from the initial
data analysis to the final written manuscript or thesis (hence the
name *Code As Manuscript*).

The `workshops` repository is where the material is developed and
sent to the website (which is on the `gh-pages` branch).

To contribute, fork the repository and submit a pull request!

# Resources for developing the lessons: #

For images, put them in the `/lessons/images` folder and reference
them within the lesson using `../images/`.

For developing lesson plans, using the pull request feature. For
maintaining the site and the repository, use direct pushing.
60 changes: 60 additions & 0 deletions about.md
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---
layout: page
title: About
sidebar: true
permalink: /
---

<p class="message">

<b>Code As Manuscript</b> is a group that teaches a series of workshops on
rethinking how code and analyses are structured, and how to
implement it. Our mission is to provide training to researchers and
scientists on how to make their analyses more reproducible and to
change how researchers view their code.

</p>

We get much inspiration for our workshops from
[Software Carpentry (SWC)](http://software-carpentry.org/), of which
we are also SWC instructors.

Currently, we teach these workshops to graduate students in our home
department and are in the process of expanding to the
[Graduate Professional Skills program](http://www.sgs.utoronto.ca/currentstudents/Pages/Professional-Development.aspx)
at the University of Toronto. Our material is in general split into
two parts:

* [Lesson content](lessons/)
* [GPS content](gps/), which also encompasses the lesson content

## Misc facts about this website ##

* Uses the [Hyde](http://hyde.getpoole.com/)
[Jekyll](http://jekyllrb.com) theme
* Developed on GitHub and hosted for free on [GitHub Pages](https://pages.github.com)
* The content on our site is [licensed](LICENSE/) under CC-BY, while
the website design is under MIT. Check out our
[license page](LICENSE/) for more info.

Have questions or suggestions? Feel free to
[open an issue on GitHub](https://github.com/codeasmanuscript/development/issues/new)
or email the *Code As Manuscript* instructors (<[email protected]>) for
more information

# Site listing and content: #

{% for cat in site.category-list %}

## {{ cat }} ##

<ul>
{% for page in site.pages %}
{% for pc in page.categories %}
{% if pc == cat %}
<li><a href="{{ site.github.url }}{{ page.url }}">{{ page.title }}</a></li>
{% endif %} <!-- cat-match-p -->
{% endfor %} <!-- page-category -->
{% endfor %} <!-- page -->
</ul>
{% endfor %}
20 changes: 20 additions & 0 deletions gps/about.md
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---
layout: page
sidebar: true
title: GPS
permalink: gps/
---

GPS, or
[Graduate Professional Skills program](http://www.sgs.utoronto.ca/currentstudents/Pages/Professional-Development.aspx),
is offered by the
[School of Graduate Studies](http://www.sgs.utoronto.ca/Pages/default.aspx)
at the University of Toronto. The goal of the program is to provide
workshops that teach students skills that may be useful in careers
after they graduate. Completing the GPS program is recorded on the
students' transcript. Our GPS-approved *Code As Manuscript* series of
workshops provide credits to completion of the GPS program. Our links
for the workshop series are:

* [Syllabus](sas-syllabus/) for our SAS workshops.
* [Syllabus](r-syllabus/) for our R workshops.
102 changes: 102 additions & 0 deletions gps/r-syllabus.md
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---
title: "Code as Manuscript: Data wrangling, visualization, and reproducibility in R"
author:
- Luke W. Johnston
- Sarah Meister
date: 2015-10-17
layout: page
sidebar: false
tag:
- GPS
- R
- Syllabus
categories:
- GPS
- R
- Syllabus
---

## Course description: ##

This series of *hands-on* workshops aims to introduce students to the
concept of research reproducibility and to get the students practicing
with using version control systems and with using modern techniques in
R that make analyses less error prone and reproducible, and that make
you more efficient, productive, and in control. Techniques for using
version control systems to faciliate greater collaboration among peers
will also be presented. The ultimate goal of the workshop is to show
how to reduce the number of steps needed to go from the initial data
analysis to the final written manuscript or thesis (hence the name
*Code As Manuscript*). Given the applied nature of the concepts in
these workshops, hands-on activities and
[live coding](http://en.wikipedia.org/wiki/Live_coding) will be
integrated into each workshop.

## Goal: ##

The expected goal of the workshops is that you will be able to:

* Put your research under version control using Git.
* Push and pull your git research repository to either
[GitHub](https://github.com/) or
[BitBucket](https://bitbucket.org/).
* Learn the basics of R and functions within R
* Produce publication quality plots
* Quickly wrangle your data into an analyzable format
* Reproducibly incorporate R code into your manuscript or thesis to
instantly add results and plots (no more copy and paste)

Attaining these goals will be the first steps in making an efficient
and highly productive workflow, that is also scientifically rigorous
and transparent, and which you can take with you for the rest of your
career (since R is free!).

## Schedule ##

Lesson content can be found [here]({{ site.github.url }}/lessons/). The workshop will
follow the following sequence of topics on **Mondays from 3:00-6:00pm** at **65
St. George St., room 201**:

1. Git & GitHub -- Oct. 26th
2. Basics of R -- Nov. 2nd
3. Visualization -- Nov. 9th
4. Data wrangling -- Nov. 16th
5. Dynamic report generation -- Nov. 23rd

## Intended audience: ##

Graduate students or post-docs whose research involves a fair amount
of data analysis. No experience necessary for these workshops.

## Pre-requisites: ##

* Fully charged laptop (though we do have outlets)
* Install the appropriate software (see our
[instructions page, under the R section]({{ site.github.url }}/lessons/instructions/))
* Bring a positive, not-afraid-of-making-mistakes-or-feeling-unsure
attitude!! Learning any language (either human or computer) is
hard work and *not* easy, but can be done!

## Assignments: ##

Because this is a hands-on workshop, at the end of each workshop, we
have an activity for you to try out. And since this is a GPS-approved
course, if you want to get a GPS credit, you will need to:

1. Come to all the workshops (though we are flexible)
2. Complete each workshop assignment and push to the shared repository
on GitHub (so we can track and view it).

Don't worry if this doesn't make sense yet. We will go over all these
details over the workshop series.

# Instructors #

Luke Johnston, MSc, PhD (c)
[email protected]

Sarah Meister, MSc (c)
[email protected]

You can contact the workshop email at: [email protected]

109 changes: 109 additions & 0 deletions gps/sas-syllabus.md
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---
title: "Code as Manuscript: Practices for Reproducibility and Efficiency in SAS"
author:
- Luke Johnston
- Daiva Nielsen
date: 2015-06-15
geometry: margin=1in
fontsize: 12pt
papersize: letterpaper
layout: page
sidebar: false
tag:
- GPS
- SAS
- Syllabus
categories:
- GPS
- SAS
- Syllabus
---

## Course description: ##

This series of workshops aims to introduce students to the concept of
research reproducibility and to get the students practicing with using
version control systems and with using techniques in SAS that make the
analysis more efficient, less error prone, and less stressful.
Techniques for using version control systems to faciliate greater
collaboration among peers will also be presented. The ultimate goal
of the workshops is to demonstrate how to reduce the total number of
steps required to produce a manuscript from the data analysis stage
(hence the name *Code As Manuscript*). Given the applied nature of
the concepts in these workshops, hands-on activities and
[live coding](http://en.wikipedia.org/wiki/Live_coding) will be
integrated into each workshop.

## Goal: ##

The expected goal of the workshops is that you will be able to:

* Put your research under version control using Git.
* Push and pull your git research repository to either
[GitHub](https://github.com/) or
[BitBucket](https://bitbucket.org/).
* Simplify your SAS code by using macros and ODS facilities in a way
that allows code to output results into a file that can be easily
incorporated into a manuscript or report.
* To put the macros into either a macro file or as a SAS autocall
library so that the macros are useable in all your SAS files.

Attaining these goals will the first steps in making an efficient and
highly productive workflow, that is also scientifically rigorous and
transparent, which you can take with you for the rest of your career.

## Schedule ##

Lesson content can be found [here]({{ site.github.url }}/lessons/). The workshop will
follow the following sequence of topics:

1. Git: June 16th, 3:00-5:00pm
2. GitHub: June 23rd, 3:00-5:00pm
3. Macros: June 30th, 3:00-5:00pm
4. ODS: July 7th, 3:00-5:00pm

## Intended audience: ##

Graduate students or post-docs whose research involves a fair amount
of data analysis using SAS.

## Pre-requisites: ##

* Bring a fully charged laptop
* Install the appropriate software (see our
[instructions page]({{ site.github.url }}/lessons/instructions/))
* Fairly competent in coding SAS commands. *We are not here to teach
an introduction to SAS*, we assume you are fairly competent with
using SAS. If you are a novice, recognize that you may not
understand everything that is going on... *However*, you will still
likely learn a lot!!
* Some familiarity with the command-line or with computing is
desirable, but not necessary.

## Assignment: ##

Because of the hands-on nature of the workshops, in order to obtain a
GPS credit for the workshops you need to:

1. Come to all the workshops
2. Complete each workshop assignment

To hand in the assignment, you will need to:

1. Fork our shared workshop repository
2. Clone it to your computer
3. Create a new folder with your name
4. Put the assignments for each workshop in your new folder
5. Commit and push the assignments to your fork
6. Submit a pull request to the main shared repository

Don't worry if this doesn't make sense yet. We will go over all these
details over the workshop series.

# Instructors #

Luke Johnston, MSc, PhD (c)
[email protected]

Daiva Nielsen, PhD
[email protected]
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