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Instructor notes #488

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Oct 16, 2023
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Instructor notes #488

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5f4255a
Add summary of Intro to R in the Narrative of instructor notes #477
juanfung Oct 2, 2023
2de4449
Added suggested lesson plans to instructor notes #477
juanfung Oct 2, 2023
ee13ef6
Changed lesson timing in Summary and Schedule to cite suggested lesso…
juanfung Oct 2, 2023
02dfb96
Fix typo instructor notes heading for Introduction to R
juanfung Oct 3, 2023
d713551
Add missing close parenthesis to Summary
juanfung Oct 3, 2023
2cf3bd8
Remove redundant link to instructor notes in index.md
juanfung Oct 12, 2023
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Move narrative notes from instructor notes to individual episodes usi…
juanfung Oct 12, 2023
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6 changes: 4 additions & 2 deletions index.md
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Expand Up @@ -8,8 +8,10 @@ less time, and with less pain. The lessons below were designed for
those interested in working with social sciences data in R.

This is an introduction to R designed for participants with no
programming experience. These lessons can be taught in a day (~ 6
hours). They start with some basic information about R syntax, the
programming experience. These lessons can be taught in a half-day,
full-day, or over a two-day workshop (see
[Instructor Notes](https://datacarpentry.org/r-socialsci/instructor/instructor-notes.html)).
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The link to the instructor notes is put in twice, once in the markdown link and once outside it. Delete the second instance.

They start with some basic information about R syntax, the
RStudio interface, and move through how to import CSV files, the
structure of data frames, how to deal with factors, how to add/remove
rows and columns, how to calculate summary statistics from a data
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37 changes: 33 additions & 4 deletions instructors/instructor-notes.md
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Expand Up @@ -2,7 +2,9 @@
title: Instructor Notes
---

## Dataset
## Narrative

### Dataset

The data used for this lesson are a slightly cleaned up version of the
SAFI Survey Results available on GitHub. The original data is on
Expand All @@ -11,8 +13,6 @@ SAFI Survey Results available on GitHub. The original data is on
This lesson uses `SAFI_clean.csv`. The direct download link for the data file is:
[https://raw.githubusercontent.com/datacarpentry/r-socialsci/main/episodes/data/SAFI_clean.csv](https://raw.githubusercontent.com/datacarpentry/r-socialsci/main/episodes/data/SAFI_clean.csv).

## Narrative

### Before we start

- The main goal here is to help the learners be comfortable with the RStudio
Expand All @@ -23,7 +23,13 @@ This lesson uses `SAFI_clean.csv`. The direct download link for the data file is
sure that learners are in the correct working directory, and that they create
a `data` (all lowercase) subfolder.

### Intro to R
### Introduction to R

- The main goal is to introduce users to the various objects in R, from atomic types
to creating your own objects.
- While this epsiode is foundational, be careful not to get caught in the weeds as the
variety of types and operations can be overwhelming for new users, especially before
they understand how this fits into their own "workflow."

### Starting with data

Expand Down Expand Up @@ -63,6 +69,29 @@ The two main goals for this lessons are:
- Note that his lesson was community-contributed and remains a work in progress. As such, it could
benefit from feedback from instructors and/or workshop participants.

## Lesson Plans

The lesson contains much more material than can be taught in a day. Instructors will
need to pick an appropriate subset of episodes to use in a standard one day course.

Suggested path for half-day course:

- Before we Start
- Introduction to R
- Starting with Data

Suggested path for full-day course:

- Before we Start
- Introduction to R
- Starting with Data
- Data Wranging with dplyr
- (OPTIONAL) Data Wrangling with tidyr
- Data Visualisation with ggplot2

For a two-day workshop, it may be possible to cover all of the episodes. Feedback from
the community on successful lesson plans is always appreciated!

## Technical Tips and Tricks

Show how to use the 'zoom' button to blow up graphs without constantly resizing
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