Discover @mark-andrews Open Source projects

Mark Andrews (@mark-andrews)

mark-andrews

Stars
210
Global Rank 118,622 (Top 5 %)
Followers 83
Following 2
Registered over 6 years ago
Most used languages

R
55.7 %

TeX
24.1 %

Jupyter Notebook
11.4 %

HTML
5.1 %

Python
2.5 %

Perl
1.3 %
Location 🇬🇧 United Kingdom
Country Total Rank 6,502
Country Ranking

TeX
75

R
90

Perl
122

Jupyter Notebook
1,336

HTML
1,860

ddsr

Source code for the book "Doing Data Science in R" by Mark Andrews (SAGE publishers, 2021)

gesis-48-bayesian-multilevel

Bayesian multilevel models course for Gesis 48. March 2019

irrs03

Introduction to statistics using R and Rstudio

immr05

Introduction to Multilevel (hierarchical, or mixed effects) Models

bayeslund2017

LaTeX source of slides for a talk given at Bayes@Lund 2017

introduction-to-R

Slides, code, etc for a workshop introducing R

immr03

Introduction to Multilevel (hierarchical, or mixed effects) Models

introduction-to-git

Introduction to Git

psyntur

Tools to help teach data analysis using R to NTU Psychology students

immr04

Introduction to Multilevel (hierarchical, or mixed effects) Models

teaching-bayes-talmo24

Slides etc for a talk on teaching Bayesian methods

bayesian_ppc

Some code and data for a workshop on posterior predictive checks

guardian-league-table-2018

Shiny/R app for viewing the Guardian university league tables

teaching_with_R_lancaster

A presentation for a meeting about teaching R in psychology departments

wlv-bayes-2022

Introduction to Bayesian data analysis

sips2019

Materials for a workshop on reproducible research at SIPS2019

bas2021datascience

A four day course on statistics and data science for the British Antarctic Survey

iglm02

Introduction to Generalized Linear Models

psypag-kent-2017

Slides and code for a talk given at PsyPAG, University of Kent, July 2017

bayes-workshop-ulisboa-2024

Workshop on Bayesian Data Analysis in University of Lisbon, January 2024

imdl03

Introduction to Machine Learning and Deep Learning using R

iglm04

Introduction to Generalized Linear Models

bayes-lmu-2018

Slides, code, etc for a workshop on Bayesian data analysis held at LMU, September 2018

ntupsystats-misc

Miscellaneous scripts, code, or data files used during statistics teaching in Psychology Department in Nottingham Trent University

bada01

Bayesian Data Analysis

irrs01

Introduction to statistics using R and Rstudio

pyml02

Introduction to Machine Learning and Deep Learning using Python

Jupyter Notebook

immr06

Workshop on multilevel/mixed-effects models

barm01

Bayesian Approaches to Regression and Mixed Effects Models using R and brms

intropy4ds

Introduction to Python for Data Science

Jupyter Notebook

iglm03

Introduction to Generalized Linear Models

msms02

Model selection and model simplification

teachstatsr-jun22

Teaching statistics with R in Psychology Symposium

pyin02

Introduction to Python and Programming in Python

Jupyter Notebook

isbd01

Introduction to Stan for Bayesian Data Analysis

irrs_ntu_doctoral_school

Info and materials for a one day training course on R and RStudio

psyc30815-202021

R and Rmd scripts, etc, for psyc30815 (2020-21)

immr02

Introduction to Multilevel (hierarchical, or mixed effects) Models

fbda01

The Fundamentals of Bayesian Data Analysis

isdsr-book

RMarkdown source for the "Introduction to Statistics and Data Science Using R" textbook

methods-hub-2023-talk

methods-hub-2023-talk

dwdv01

Introduction to Data Wrangling and Data Visualization using R

rsdwr

Data wrangling and RMarkdown-based reproducible reports using R

gamr01

Nonlinear Regression using Generalized Additive Models

bnctools-project

Python etc tools for working with the British National Corpus

intro-to-brms

A gentle and brief introduction to brms

msms03

Workshop on model selection and evaluation

gnam02

Nonlinear regression using R: Generalized Linear Models, Generalized Additive Models, Basis function regression, Gaussian processes, and other methods.

pyin03

Introduction to Python

dvgg01

Introduction to Data Visualization using R

dwrs01

Introduction to Data Wrangling using R

msms01

Model selection and model simplification

bpsconf2018

Slides etc accompanying a spoken presentation at BPS annual conference, May 2, 2018.

Jupyter Notebook

pspy01

Some notebook etc for a workshop on Python

Jupyter Notebook

repdemoproj

A demo reproducible data analysis project

intro_bda_qub

Introduction to Bayesian Data Analysis

iglm01

Introduction to Generalized Linear Models

dwrs02

Introduction to Data Wrangling using R

project101

A demo repository for teaching and training purposes only

gnam01

RMarkdown, slides, data, etc for a workshop on generalized linear and generalized additive models

psbayes

Slides, code, etc for a workshop on Bayesian data analysis (psstatistics, December 2018)

cheater-profile

Demo of how to calculate class conditional probabilities using logistic regression

BayesianAccountMemoryText

Code, data, manuscript related to a research project on a Bayesian account of memory for text

Jupyter Notebook

intro2brms

Introduction to brms

bps-introduction-to-R

Slides and RMarkdown files for an Introduction to R workshop

imdl01

Two day course on Introduction to Machine Learning and Deep Learning using R

qsort-shiny-app

rdrp01

Reproducible Data Science using RMarkdown, Git, R packages, Docker, Make, and other tools

imdl02

Introduction to Machine Learning and Deep Learning using R

dvgg02

Introduction to Data Visualization using R

psyc20255managementproject

Python tools for the management of the psyc20255 module at Nottingham Trent University.

intro2pystats

Introduction to data analysis and statistics using Python

Jupyter Notebook

pyml01

Introduction to Machine Learning and Deep Learning using Python

Jupyter Notebook

lancaster-bayes-workshop

A workshop on Bayesian methods at Lancaster University, June 2018

ntu-doctoral-rrstudio

Materials for course on R and RStudio

share_rmd_html_privately

A demo of a password protected html page in GitHub pages

immr23

Introduction to Multilevel, Hierarchical, or Mixed Effects Models using R

tilt_roundtable

Slides for event on writing textbooks

psyntur_in_binder

R/RStudio project for mybinder

ljmu_multilevel_models

Training course on multilevel models

research-integrity-2017

Slides for my talk entitled *Open, transparent, and reproducible research with RMarkdown, Jupyter notebooks, and Git* delivered at the Improving research integrity and reproducibility through openness and transparency symposium held in UCC, Oct 23, 2017.

pysc01

Introduction to Scientific, Numerical, and Data Analysis Programming in Python

Jupyter Notebook

bps-cogdev19-ans

Slides on using HDDM to analyse ANS

esslli-2017-bayesian-methods

Materials for Bayesian Methods for Language Sciences, a course taught at 29th European Summer School in Logic, Language, and Information, University of Toulouse (France), 17-28 July, 2017