excelnumericaldemos

A set of numerical demonstrations in Excel to assist with teaching / learning concepts in probability, statistics, spatial data analytics and geostatistics. I hope these resources are helpful, Prof. Michael Pyrcz

https://github.com/geostatsguy/excelnumericaldemos

Science Score: 77.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
    Links to: scholar.google, zenodo.org
  • Committers with academic emails
    1 of 1 committers (100.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.3%) to scientific vocabulary

Keywords

dataanalytics excel geostatistics machinelearning
Last synced: 6 months ago · JSON representation ·

Repository

A set of numerical demonstrations in Excel to assist with teaching / learning concepts in probability, statistics, spatial data analytics and geostatistics. I hope these resources are helpful, Prof. Michael Pyrcz

Basic Info
  • Host: GitHub
  • Owner: GeostatsGuy
  • License: mit
  • Default Branch: master
  • Homepage:
  • Size: 13.9 MB
Statistics
  • Stars: 111
  • Watchers: 7
  • Forks: 51
  • Open Issues: 3
  • Releases: 1
Topics
dataanalytics excel geostatistics machinelearning
Created over 8 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

ExcelNumericalDemos: Educational Data Science Excel Demonstrations Repository (0.0.1)

Interactive dashboards to help you over the intellectual hurdles of data science!

If you can't explain it simply, you don't understand it well enough - Alberta Einstein

To reach more students and working professionals with my *Data Analytics and Geostatistics, **Spatial Data Analytics and Machine Learning courses, I have developed a set of Excel interactive dashboards. When students struggle with a concept I make a new interactive dashboard so they can learn by playing with the statistics, models or theoretical concepts, and virtually everyone has Excel!*

Michael Pyrcz, Professor, The University of Texas at Austin, Data Analytics, Geostatistics and Machine Learning

Twitter | GitHub | Website | GoogleScholar | Book | YouTube | LinkedIn


Cite As:

Pyrcz, Michael J. (2021). ExcelNumericalDemos: Educational Data Science Excel Demonstrations Repository (0.0.1). Zenodo. https://zenodo.org/doi/10.5281/zenodo.5564991

DOI


Setup

A minimum environment includes:

  • Microsoft Excel > 2010 - note, VBA is not required

Datasets are embedded in the Excel files.

Repository Summary

To me 'coding up' or 'building out' a method or workflow in Excel without VBA is the ultimate case of explaining it simply! So while I do code in FORTRAN, C++ (20 years experience), VBA, R and Python, I challenge myselt to put methods and workflows in Excel to provide hands-on experiential learning that reaches more students. Why do I feel this way?

  • Assessibility - in STEM everyone has access to Excel. This is even more true with the online applications Microsoft now provides and the vast majority of scientists and engineers know the basics of working with Excel
  • Interpretability - one can easily interogate a method or workflow in Excel, just click on the cell to see the equation
  • Set Up - there is no set up needed to get students started with these demonstrations

I teach in a lot of places and I teach a lot of things. I adjust to get the job done. Now, if you are convinced that I'm old fashion, check out my:

The Author:

Michael Pyrcz, Professor, The University of Texas at Austin

Novel Data Analytics, Geostatistics and Machine Learning Subsurface Solutions

With over 17 years of experience in subsurface consulting, research and development, Michael has returned to academia driven by his passion for teaching and enthusiasm for enhancing engineers' and geoscientists' impact in subsurface resource development.

For more about Michael check out these links:

Twitter | GitHub | Website | GoogleScholar | Book | YouTube | LinkedIn

Want to Work Together?

I hope this content is helpful to those that want to learn more about subsurface modeling, data analytics and machine learning. Students and working professionals are welcome to participate.

  • Want to invite me to visit your company for training, mentoring, project review, workflow design and / or consulting? I'd be happy to drop by and work with you!

  • Interested in partnering, supporting my graduate student research or my Subsurface Data Analytics and Machine Learning consortium (co-PIs including Profs. Foster, Torres-Verdin and van Oort)? My research combines data analytics, stochastic modeling and machine learning theory with practice to develop novel methods and workflows to add value. We are solving challenging subsurface problems!

  • I can be reached at mpyrcz@austin.utexas.edu.

I'm always happy to discuss,

Michael

Michael Pyrcz, Ph.D., P.Eng. Professor, Cockrell School of Engineering and The Jackson School of Geosciences, The University of Texas at Austin

More Resources Available at: Twitter | GitHub | Website | GoogleScholar | Book | YouTube | LinkedIn

Owner

  • Name: Michael Pyrcz
  • Login: GeostatsGuy
  • Kind: user
  • Location: Austin, TX, USA
  • Company: @UTAustin

Full Professor at The University of Texas at Austin working on Spatial Data Analytics, Geostatistics and Machine Learning

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this data repository, please cite it as below."
authors:
  - family-names: Pyrcz
    given-names: Michael J.
    orcid:  https://orcid.org/0000-0002-5983-219X 
title: "ExcelNumericalDemos: Educational Data Science Demonstrations Repository"
version: 1.0.0
doi: 10.5281/zenodo.5564991
date-released: 2021-10-12

GitHub Events

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  • Watch event: 6
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Last Year
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Last synced: about 2 years ago

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  • Total Committers: 1
  • Avg Commits per committer: 89.0
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Michael Pyrcz m****z@a****u 89
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Last synced: 9 months ago

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  • Average comments per issue: 1.0
  • Average comments per pull request: 0
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Past Year
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  • Pull requests: 0
  • Average time to close issues: N/A
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  • Issue authors: 0
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  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
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