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Adjusted for editing on ACC computer
Tried to define dependencies for an env, called moda_env. The dabest version is outdated. Checked that the code worked with the listed environment.yml dependencies list. Added UNIX to the suggested reading.
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‎environment.yml‎

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name: moda_env
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channels:
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- defaults
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dependencies:
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- python=3.10
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- pip
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- pip:
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- fastcore
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- pandas>=1.5.0,<2.0.0
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- numpy>=1.22.3,<1.23.0
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- matplotlib~=3.5.1 # Adjusted to match dabest's requirement
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- seaborn==0.11.2 # Pin seaborn to a version compatible with dabest
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- scipy>=1.9.3,<2.0.0
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- dabest>=2023.2.14,<2024.0.0
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- scikit-learn
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- statsmodels
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- palmerpenguins
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- jupyter

‎nbs/01_Introduction.ipynb‎

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"session, we offer a basic orientation on these topics."
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]
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "19964860-2836-43b1-963e-063dfe336287",
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"metadata": {},
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"outputs": [
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"data": {
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"text/html": [
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"<iframe width=\"600\" height=\"400\"\n",
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"src=\"https://www.youtube.com/embed/kgicuytCkoY\">\n",
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"</iframe>\n"
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],
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"%%HTML\n",
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"<iframe width=\"600\" height=\"400\"\n",
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],
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"metadata": {
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‎nbs/03_Data_Analysis_with_Jupyter_and_Python.ipynb‎

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‎nbs/05_Additional_resources.ipynb‎

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"id": "4dc195ef",
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"metadata": {},
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"source": [
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"## Additional resources and building your skills\n",
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"## Key resources: A self-guided course in data science\n",
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"\n",
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"Try using the [estimationstats.com](https://www.estimationstats.com/#/) web app to analyze your own grouped data.\n",
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"\n",
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"Open and have a look at the sample multivariate\n",
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"[data](https://docs.google.com/spreadsheets/d/1F0c5I_S9_NnLKPMQxJkEfzGfhzQeR26SgkiHSTFwKDE/edit?usp=sharing).\n",
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"Go through the [introductory\n",
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"notebook](https://drive.google.com/file/d/1m_l4k5ZaUc03hpvcfBd_Riy2nXYDpFXg/view?usp=sharing)\n",
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"that demonstrates data analysis.\n",
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"- Coding: There are many online resources to learn coding. Published\n",
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" in 2021, [A Data-Centric Introduction to\n",
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" Computing](https://dcic-world.org/) uses a Python-like teaching\n",
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" language ([Pyret](https://www.pyret.org/)) to introduce key concepts\n",
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" in computer science.\n",
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"\n",
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"We recommend the following texts to strengthen your data-analysis and\n",
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"presentation skills. They can be dipped into over the coming months or\n",
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"years, and used as references. Being familiar with some or all of this\n",
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"material will help you write your first-author paper/s and doctoral\n",
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"thesis.\n",
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"- The command-line interface: You will want to learn the command line interface, we recommend [The basics of working on the UNIX command line](https://computing.stat.berkeley.edu/tutorial-unix-basics/index.html) to start. Continue with the [Bash shell tutorial](https://computing.stat.berkeley.edu/tutorial-using-bash/index#1-this-tutorial).\n",
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"\n",
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"### *Key resources*\n",
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"- A text on data visualization: Claus Wilke’s free online\n",
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" [book](https://clauswilke.com/dataviz/index.html) is a great\n",
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" introduction to data visualization, and a style guide. It is written\n",
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" in R, which is the best language for statistics.\n",
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"\n",
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"- Estimation: Our\n",
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" [estimationstats.com](https://www.estimationstats.com/#/background)\n",
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" and [effect\n",
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" sizes](https://www.estimationstats.com/#/about-effect-sizes).\n",
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"\n",
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"- Datavis: Claus Wilke’s free online\n",
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" [book](https://clauswilke.com/dataviz/index.html) is a great\n",
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" introduction to data visualization, and a style guide. It is written\n",
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" in R, which is the best language for statistics.\n",
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"### Additional resources\n",
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"\n",
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"- Coding: There are many online resources to learn coding. Published\n",
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" in 2021, [A Data-Centric Introduction to\n",
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" Computing](https://dcic-world.org/) uses a Python-like teaching\n",
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" language ([Pyret](https://www.pyret.org/)) to introduce key concepts\n",
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" in computer science.\n",
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"Try using the [estimationstats.com](https://www.estimationstats.com/#/) web app to analyze your own grouped data.\n",
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"\n",
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"Open and have a look at the sample multivariate\n",
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"[data](https://docs.google.com/spreadsheets/d/1F0c5I_S9_NnLKPMQxJkEfzGfhzQeR26SgkiHSTFwKDE/edit?usp=sharing).\n",
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"Go through the [introductory\n",
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"notebook](https://drive.google.com/file/d/1m_l4k5ZaUc03hpvcfBd_Riy2nXYDpFXg/view?usp=sharing)\n",
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"that demonstrates data analysis.\n",
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"\n",
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"### *Additional resources*\n",
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"We recommend the following texts to strengthen your data-analysis and\n",
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"presentation skills. They can be dipped into over the coming months or\n",
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"years, and used as references. Being familiar with some or all of this\n",
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"material will help you write your first-author paper/s and doctoral\n",
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"thesis.\n",
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"\n",
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"#### *Some are free, some you will need to buy or borrow from the library.*\n",
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"#### Further reading: Some are free, some you will need to buy or borrow from the library.\n",
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"\n",
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"- Estimation: If you want to learn about estimation statistics in\n",
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" greater depth, there is Calin-Jageman and Cumming’s\n",
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"%%HTML\n",
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"</iframe>"
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‎nbs/index.ipynb‎

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"source": [
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"**This material is used in Duke-NUS Medical School classes:**\n",
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"* GMS6812: Foundations of Precision Medicine hands-on workshops for the PhD programme in Clinical and Translational Sciences.\n",
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"* IBM Ethics and Personal and Professional Development Session"
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"* Duke-NUS PhD programme in Integrated Biology and Medicine. Ethics and Personal and Professional Development Sessions"
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]
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},
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{
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"\n",
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"If we have more time in class, you will also be introduced to our estimation statistics package [DABEST Introduction](dabest_introduction.html).\n",
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"\n",
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"If you have any questions about these materials, please contact `xusangyu at gmail.com`\n"
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"If you have any questions about these materials, please contact your course coordinator.\n"
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]
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{
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],
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"metadata": {
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"kernelspec": {
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.16"
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},
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"nbformat": 4,

‎nbs/myplot.png‎

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