https://github.com/openintrostat/oilabs-stata
👩🏿💻 OpenIntro Labs in Stata
https://github.com/openintrostat/oilabs-stata
Last synced: 4 months ago
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👩🏿💻 OpenIntro Labs in Stata
- Host: GitHub
- URL: https://github.com/openintrostat/oilabs-stata
- Owner: OpenIntroStat
- License: other
- Created: 2018-05-29T11:15:18.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2023-11-19T03:32:24.000Z (over 2 years ago)
- Last Synced: 2024-03-25T21:19:58.744Z (about 2 years ago)
- Language: HTML
- Homepage: https://openintrostat.github.io/oilabs-stata/
- Size: 43.7 MB
- Stars: 3
- Watchers: 2
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
OpenIntro Labs - Stata
==============
OpenIntro Labs promote the understanding and application of statistics through
applied data analysis. Labs are titled based on topic area, which correpond to
particular chapters in all three versions of OpenIntro Statistics, a free and
open-source textbook. The textbook as well as the html version of the labs can
be found at [http://www.openintro.org/stat/labs.php](http://www.openintro.org/stat/labs.php).
This repository is a fork of the tidyverse OpenIntro labs, converted to Stata by
[Jenna Krall](https://github.com/kralljr). Information about the datasets can be
found in the [
-tidy](https://github.com/OpenIntroStat/oilabs-tidy) repository.
We currently support our source files in the .Rmd format, which can be output into
html format (though output to pdf is also possible). The source files are processed
using the [knitr](http://yihui.name/knitr/) package in R.
Stata must be installed to edit and recompile the labs.
To update the Stata labs, you need to first install the `statamd` package in R
from [https://github.com/muschellij2/statamd](https://github.com/muschellij2/statamd):
```
library(devtools)
install_github("muschellij2/statamd")
```
It is our hope that these materials are useful for instructors and students of
statistics. If you end up developing some interesting variants of these labs or
creating new ones, please let us know!
## Labs
1. [Introduction to Stata](https://openintrostat.github.io/oilabs-stata/01_intro_to_stata/intro_to_stata.html)
1. [Introduction to data](https://openintrostat.github.io/oilabs-stata/02_intro_to_data/intro_to_data_stata.html)
1. [The normal distribution](https://openintrostat.github.io/oilabs-stata/03_normal_distribution/normal_distribution_stata.html)
1. [Probability](https://openintrostat.github.io/oilabs-stata/04_probability/probability_stata.html)
1. [Foundations for statistical inference - Sampling distributions](https://openintro.shinyapps.io/sampling_distributions_stata/)
1. [Foundations for statistical inference - Confidence intervals](https://openintrostat.github.io/oilabs-stata/06_confidence_intervals/confidence_intervals_stata.html)
1. [Inference for numerical data](https://openintrostat.github.io/oilabs-stata/07_inf_for_numerical_data/inf_for_numerical_data_stata.html)
1. [Inference for categorical data](https://openintro.shinyapps.io/inf_for_categorical_data_stata/)
1. [Introduction to linear regression](https://openintrostat.github.io/oilabs-stata/09_simple_regression/simple_regression_stata.html)
1. [Multiple linear regression](https://openintrostat.github.io/oilabs-stata/10_multiple_regression/multiple_regression_stata.html)
## Feedback / collaboration
Your feedback is most welcomed! If you have suggestions for minor updates (fixing
typos, etc.) please do not hesitate to issue a pull request. If you have ideas for
major revamp of a lab (replacing outdated code with modern version, overhaul in
pedagogy, etc.) please create an issue so to start the conversation.