Analyses II
Contents
Analyses II¶
With this session, we conclude the final chapter of our endeavor. After spending quite a good while on basic data handling and data wrangling, we will continue with data visualization and data analyses using python. This includes a brief showcase of several distinct aspects/steps in a “classic” data analyses workflow: data visualization for explorative and statistical purposes, as well as statistical analyses. As usual the aim is to provide folks a respective overview that allows them to dig further into details and start using python for their data analyses after the course ends.
Topics 💡👨🏻🏫¶
In the following you’ll find the objectives and materials for each of the topics we’ll discuss during this session.
Introduction to Data analyses - II¶
Sure, most of us already conducted some analyses here and there but did you already make use of the fantastic world of data analyzes using python with its tremendously powerful go-to modules and basically unlimited amount of highly specialized libraries? No matter what you’re looking for and want to work on, python’s got your back! Given the short amount of time we have, this session will focus on one of the central modules concerning data visualization and statistical analyses. In more detail, we will visualize and analyse the data we obtained during the PsychoPy sessions via different means.
Objectives 📍¶
learn basic and efficient usage of python for data analyzes & visualization
working with data:
reading, working, writing
preprocessing, filtering, wrangling
visualizing data:
basic plots
advanced & fancy stuff
statistical analyses
Ask and answer questions
Have a great time
Materials 📓¶
Please see the rendered version of the jupyter notebook Data analyzes II - data visualization and analyses in the ToC on the left.
tasks for subsequent meeting 🖥️✍🏽📖¶
Your ninth homework assignment will entail working through a few tasks covering the contents discussed in this session within of a jupyter notebook. You can download it here. In order to open it, put the homework assignment notebook within the folder you stored the course materials, start a jupyter notebook as during the sessions, navigate to the homework assignment notebook, open it and have fun!
Deadline: 16/02/2022, 11:59 PM EST
Optional: If you are interested in using python for a specific task/problem/analyses/etc. or have general questions, please send us a message before the class or outline them to ask during the class, as we will do a general Q&A and provide some pointers on how to continue and extent your python adventures!
optional/reading/further materials¶
Here’s a cool add-on to further familiarize yourself with seaborn and its capabilities.
If you want to learn more about statistics in python, check this video: