Summary and Setup

In this lesson, you’ll explore the different types of graphs and their use cases. You’ll then dive into the concept of statistical inference. Next, you’ll get hands-on with Python coding to analyze the happiness and income dataset provided below. Finally, you’ll use the graphs you’ve created to make informed estimates about countries not included in the dataset.

What background knowledge do you need for this lesson?

  1. Basic acquaintance with Python: you should know how to import Python packages and load data into your code. You also need basic familiarity with Python syntax.
  2. Basic mathematical background: you need a basic understanding of statistics and probabilities.
  3. Curiosity to learn more about Python programming, statistics and data storytelling

Dataset

The dataset we are working with in this lesson originates from Kaggle. If you wish to save the the dataset on your computer, go ahead and download the Income and Happiness Correlation dataset and save it to your working directory. Otherwise, you can directly load it into your code later using the following link:

https://raw.githubusercontent.com/HERMES-DKZ/stat_inf_data_vis/main/episodes/data/income_happiness_correlation.csv

Software Setup

Python and Jupyter Notebook/Google Colab

To do the exercises in this lesson, you need an IDE (Integrated Development Environment). We recommend you use Jupyter Notebook or cloud-based equivalent such as Google Colab.

If you’re using Google Colab, you don’t need any installation. Just create a Google account - if you don’t have one already -, create a new Colab Notebook by clicking on New Notebook in the above link, and start coding.

Otherwise, to install Jupyter Notebook and Python on your computer together, we recommend using Anaconda. To do so, click on your operating system from the list below and follow the instructions.

  1. Open https://www.anaconda.com/download/success with your web browser.
  2. Download the Anaconda for Windows installer with Python 3. (If you are not sure which version to choose, you probably want the 64-bit Graphical Installer Anaconda3-…-Windows-x86_64.exe.)
  3. Install Python 3 by running the Anaconda Installer, using all of the defaults for installation except make sure to check Add Anaconda to my PATH environment variable.

This video tutorial can help you with the installation.

  1. Open https://www.anaconda.com/download/success with your web browser.
  2. Download the Anaconda Installer with Python 3 for macOS (you can either use the Graphical or the Command Line Installer).
  3. Install Python 3 by running the Anaconda Installer using all of the defaults for installation.

This video tutorial can help you with the installation.

  1. Open https://www.anaconda.com/download/success with your web browser.
  2. Download the Anaconda Installer with Python 3 for Linux. (The installation requires using the shell. If you aren’t comfortable doing the installation yourself stop here and request help at the workshop.)
  3. Open a terminal window and navigate to the directory where the executable is downloaded (e.g., cd ~/Downloads).
  4. Type bash Anaconda3- and then press Tab to autocomplete the full file name. The name of file you just downloaded should appear.
  5. Press Enter (or Return depending on your keyboard). You will follow the text-only prompts. To move through the text, press Spacebar. Type yes and press Enter (or Return) to approve the license. Press Enter (or Return) to approve the default location for the files. Type yes and press Enter (or Return) to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).
  6. Close the terminal window.

After installing Python and Anaconda, make sure to install the Python libraries that we are using in this lesson. If you haven’t installed Python libraries on your computer before, ask the instructors for support.