Acknowledgments

Acknowledgments#

First of all, I owe a great debt of gratitude to Aaron J. Newman of Dalhousie University for sharing his excellent open-source textbook, Data Science for Psychology and Neuroscience - in Python. What you see now is largely an edited/remixed/adapted version of the original book, one that I hope will best suit undergraduate Kinesiology students at the University of British Columbia. Much of the original work has largely been kept intact, although a couple of notable changes include substituting the chapters on EEG and MRI data with one on signal processing, as well as the addition of a section on writing functions and a chapter on statistical inference and bootstrapping (see below). My goal is that this book will evolve and take on a life of its own over iterations of teaching the course and serve as a useful, open resource for those studying and researching human movement.

There are others whose work I have also adopted (and adapted) and to whom I am very grateful:

Disclaimer#

(August 27, 2024) This book is currently a work-in-progress, and I expect to make minor edits to it over the coming weeks/months/years. Don’t be thrown off if it looks slightly different the next time you view it. Also, if you find any errors (for which I claim sole responsibility), or have suggestions, please let me know by opening an Issue on GitHub (click the Octocat icon in upper right).

Thanks,
Hyosub

License for this book#

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Suggested attribution:
Data Science for Kinesiology by Hyosub Kim. Adapted from Aaron J. Newman’s Data Science for Pyschology and Neuroscience and published under a Creative Commons Attribution-ShareAlike 4.0 International License.