💪🏻 Under development
In this lab, you will be using Git and Github to fork, clone, commit, and push changes to a repository. The repository you will select to use as the repository to fork to your own Github account can be one of the following:
If you are starting with a new repository, fork and clone the repository you selected to your local machine. Then orient yourself to the repository by opening the README file and reviewing the template configuration.
If you are using an existing reproducible research project repository, open that project on your local machine, and pull
the latest changes from the remote repository to ensure that your local and remote repositories are in sync.
Open a Quarto document in the process directory and name it accordingly (e.g., 4_analysis.qmd
, analysis.qmd
, etc.).
The data you select to explore should be in a format conducive for performing statistical inference for a specific hypothesis. The options include the following:
In your analysis process file,
add a section which provides a brief description of the dataset you will be using and the analysis setup and hypothesis. Include:
add a section which provides a description of the explanatory variables you will use and how they are operationalized. Include:
add a section which provides a description of the modeling process you will be using to conduct the analysis. Include:
Implement and make sure to organize your analysis process in a way that is reproducible. This means that you should be able to run the code in your process file and reproduce the process (use set.seed()
for any sampling process, for example). Use the data/analysis
(or similar) directory to store any derived datasets used in the analysis.
Make sure that your code is well documented with code comments and that you have included prose to describe the process of analyzing the dataset.
Include a section to describe the results of your analysis. This will minimally contain the model estimates, $p$-values, and confidence intervals and may contain effect size and/ or variance explained measures.
Confirm that your code runs without errors and that the code, visualizations, and/ or tables are displayed as expected.
Finally, commit and push your changes to your Github repository. Make sure to include files or directories that you do not have permission to share in your .gitignore
file.
Some questions to consider:
Transform the ENNTT data so that the dataset is in the following format.
doc_id | doc_type | syntactic_complexity_1 | syntactic_complexity_2 | ... |
---|---|---|---|---|
1 | native | 0.1 | 0.2 | ... |
2 | native | 0.3 | 0.4 | ... |
3 | translation | 0.5 | 0.6 | ... |
4 | translation | 0.7 | 0.8 | ... |
: Table 1: Example of the transformed ENNTT data