Summary and Schedule
This is a new lesson built with The Carpentries Workbench.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Introduction |
What is this all
about? :::::::::::::::::::::::::::::::::::::::::::::::: |
| Duration: 00h 05m | 2. R Setup |
What is R, what is R Studio? How to work with the R console and R scripts? What is an R package? ::: |
| Duration: 00h 20m | 3. Packages in R |
What is an R package? How can we use R packages |
| Duration: 00h 34m | 4. Vectors and variable types |
How do you use scripts in R to document your work? How can you organize scripts effectively? What is a vector? |
| Duration: 00h 59m | 5. Projects |
What is an R project? How do projects help me organize my scripts. |
| Duration: 01h 14m | 6. Data Visualization (1) |
How can you get an overview of data? How do you visualize distributions of data? |
| Duration: 01h 34m | 7. Data Visualization (2) |
How can you visualize categorical data? How to visualize the relationship of categorical and numerical data? |
| Duration: 01h 54m | 8. Filtering data |
How do you filter invalid data? How do you chain commands using the pipe %>%?How can I select only some columns of my data? |
| Duration: 02h 19m | 9. Creating new columns |
What function is used to create new columns in a dataset? How can you generate a unique ID column for each row? How can you modify an existing column? How can you compute an average value over many columns in your data? |
| Duration: 02h 49m | 10. Count and Summarize |
How does count() help in counting categorical data?How do you compute summary statistics? How can you use group_by() to compute summary statistics for specific
subgroups?Why is it useful to combine count() with
filter()?How can you compute relative frequencies using group_by() and mutate()?
|
| Duration: 03h 14m | 11. Midterms | No new questions today, only application |
| Duration: 03h 38m | 12. t-Test |
When can I use a t-test? What type of t-test should I use? How can I run a t-test in R? How should I interpret the results of a t-test |
| Duration: 03h 51m | 13. Factor Analysis - Introduction & EFA |
What is a factor analysis? What is the difference between exploratory and confirmatory factor analysis? How can I run exploratory factor analysis in R? How can I interpret the results of an EFA in R? |
| Duration: 04h 16m | 14. Factor Analysis - CFA |
What is a confirmatory factor analysis? How can I run CFA in R? How can I specify CFA models using lavaan? How can I interpret the results of a CFA and EFA in R? |
| Duration: 04h 41m | 15. Factor Analysis - Advanced Measurement Models |
What is a bifactor model? What is a hierachical model? How can I specify different types of measurement models? |
| Duration: 05h 06m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
In order to follow this lesson you will require 2 things: R and RStudio. R is the actual programming language. It translates the commands you write into something your computer can understand. RStudio is just a shiny new hood on R. It is more user-friendly and provides some useful tools to write and organize R code. We will learn more about these tools during the course.
For now, it is important that you download both of these tools:
Software Setup
R
To download R, go to CRAN, the comprehensive R archive network, https://cloud.r-project.org. A new major version of R comes out once a year, and there are 2-3 minor releases each year. It’s a good idea to update regularly. Upgrading can be a bit of a hassle, especially for major versions that require you to re-install all your packages, but putting it off only makes it worse. I recommend you download the latest version of R (currently R-4.4.2).
RStudio
RStudio is an integrated development environment, or IDE, for R programming, which you can download from https://posit.co/download/rstudio-desktop/. RStudio is updated a couple of times a year, and it will automatically let you know when a new version is out, so there’s no need to check back. It’s a good idea to upgrade regularly to take advantage of the latest and greatest features.
When you start RStudio, you’ll see two key regions in the interface: the console pane and the output pane. For now, all you need to know is that you type the R code in the console pane and press enter to run it. You’ll learn more as we go along!
Data
We will make use of some data available in R packages as well as data from real experiments run by me or my colleagues.
I will provide the data you need at each time point, you can then easily download the required data. If you want to download all data beforehand, download the data zip file and unzip it to your desktop.