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tutorials.qmd
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---
title: "Tutorials Overview"
---
::: {.callout-caution title="Under Construction"}
Many of the tutorials are still incomplete or under construction. If you encounter a banner like this, just check back another time!
:::
## Using the Tutorials
These tutorials are designed to accompany live training sessions, but they also serve as quick-reference guides for all the material covered in those sessions.
### Opening the Tutorials
In live sessions, it is recommended to open the corresponding tutorial in the Viewer pane in Posit Cloud so that solutions and explanations are easily available. The workbook documents provided for each week will already contain the code to do this.
However, the tutorials can also be easily accessed at any time through this website, so it isn't necessary to open Posit Cloud to view them - simply use the sidebar to jump to the tutorial you want!
### Exercises
The exercises are designed to build your skills in R. Some will ask you to try something you might not know how to do. Just give it your best shot, and if you get stuck, solutions and explanations are always provided!
::: {.callout-important title="Don't Skip the Exercises!"}
It is **strongly** recommended that you don't skip the exercises. Try each one, even if it seems completely trivial, or too hard. You will learn R much faster and more thoroughly by getting your hands dirty.
:::
All data and workbooks will be provided on Posit Cloud for completing the exercises.
#### Challenges
Some exercises will be clearly labeled as "Challenges". These exercises are **optional** and are meant to go beyond the core tutorial material. However, if you skip them, you will still be able to understand everything that follows; you won't need to complete them in order to proceed.
## Content
::: callout-tip
Looking for a particular topic or function? Use the [Quick Reference](quick_ref.qmd) to find what you need!
:::
Tutorials are divided into two rough sections.
The **first half** of the course (Tutorials 1 - 6) covers essential basic skills in R, and is designed for absolute beginners who have never seen R before and who have little to no coding experience of any kind. It focuses on working with datasets using {tidyverse} as well as introducing a variety of common statistical tests. This portion of the course ends with some hands-on practice with reproducible analysis.
By the end of this series, you will be able to:
- Navigate the RStudio IDE
- Create and work with different types of data
- Work with objects and functions
- Perform calculations and logical tests on single values and vectors
- Read in data from a .csv file into a tibble
- View and summarise the data in a tibble
- Filter cases and select variables, including efficient `<tidyselect>` semantics
- Create new variables in a dataset, or change/recode existing ones
- Create a variety of customised data visualisations
- Perform and efficiently report the results of *t*-tests, chi-squared tests, correlations, and simple and hierarchical linear models
The **second half** of the course (Tutorials 7 - 10) is focused on broadening skills in R, and is designed for those with some proficiency in R (or who have completed the first half of the course!). It focuses on working with different types of datasets, creating beautiful tables and figures, and developing reproducible data analysis skills, with the aim of building a diverse toolbox of R skills. This portion of the course ends with a detailed, step-by-step walkthrough of reproducible data analysis.
By the end of this series, you will be able to:
- Create custom data summaries and output nicely formatted summary tables
- Create powerful data visualisations
- Work with labelled data, especially from SPSS/Qualtrics, to generate data dictionaries
- Prepare large and complex datasets for data analysis
- Work with a new dataset from beginning (reading in, inspecting, cleaning) to end (wrangling, visualising, analysing, reporting)
- Analyse, report, and submit for checking a complete reproducible analysis