Resources

Useful Resources for Social Science Research /  by Flavio Azevedo

 

The list of resources below is intended for (my) personal use. It contains primers, tutorials, guides I have used/encountered and/or want to learn more about it. These are related to producing better science, open-science, methods, statistics, visualization, R & RStudio.

 
 
 
 
 

Statistics

Statistical practice

Study Design

degrees of freedom

Power Analysis

Multilevel design

Robust methods

 

Linear & Generalized Linear Models

Time Series

Causal Inference in graphs with Animated (GIF) Plots

 Survey Methodology PODCASTs

 
 
 
 

Scientific Debates

Bayesians vs. Frequentists [in social media]

 
 

R & oPEN sCIENCE

Reproducible Research

 

 

r Resources

R-Intros

 

R-Series: Complete COurses

Data Science Methods for Psychology - University of Oregon (HardSci)

Data Science for Social Sciences

Nifty Tricks & Tips

Data Visualization

Intro

R-packages

Publication geared

  • ggally: the ally of ggplot2 (display of multiple regression coefficients and its diagnostics, networks, time-series, distributions, etc.).

  • ggstatsplot: Plots with Statistical Details (most common types of statistical tests (parametric, non-parametric, and robust versions of t-tets, anova, correlation, and contingency tables)

  • ggpubr: ggplot2 based publication ready plots [tutorial at sthda]

  • cowplot: publication-ready theme for ggplot2 (e.g., easy add panels A, B, C). Here's code for adding panels to non-ggplot2 R-base graphs.

Guides

Colors and Pallets 

miscellaneous

Per type of data

Distributions 

  • ggpairs: Visualizing distributions with groupings [examples: 1]

Group differences

Time Series

Strings

Blogdown

Bookdown

 
 

[Scholarly]Social Media

 
 

Philosophy of Science

Primer on Philosophy of Science

On Karl Popper

Pot-pourri

  • Bias - list thereof with examples.

 

Everything else

Economics (Behavioral)

 

Writing

R Journalism - Reproducible Journalism by Washington Post Investigative Data Reporter

Political Science

Learning Statistics on Youtube /  by Flavio Azevedo

Youtube.com is the second most accessed website in the world (surpassed only by its parent, google.com). It has a whopping 1 billion unique views a month. [1, 2] It is a force to be reckoned with. In the video sharing platform, there are many brilliant and hard-working content creators producing high-quality and free educational videos that students and academics alike can enjoy. I made a survey on Youtube content that could be useful for those interested in learning Statistics, and I listed and categorized them below.

Truth be told, this post is a glorified Google search in many respects. In any case, I had intended for a long time to gather this information as to facilitate the often laborious task of finding pertinent resources for learning statistical science in a non-static format (i.e., videos) that is easily accessible, high-quality, instructive and free. 

Another motivation had to do with my teaching obligations. In this fall, I will teach a graduate course in Stats with R. To this end, I considered becoming a content creator myself, as to allow students to access the course's content from the convenience of their homes. In this process, I found some excellent statistical courses on Youtube. Some were really useful in terms of their organization, others in terms of content, interesting explanations, pedagogical skills, availability of materials, etc. Altogether, searching for resources was a very instructive experience, whose fruits should be shared.

Importantly, in this process, I learned that youtube is not short of 'introductory course on ___.' Not of Statistics, Probability or R, anyways. Which is a good thing. And often, you even see these three together. Also in abundance, are courses on the ABC's of probability theory, classical statistics (i.e., up to ANOVA, ANCOVA), and on basics of applied statistics (e.g., Econometrics, Biostatistics, and Machine Learning). Indeed, Machine Learning (mostly through Data Science) is really well represented on Youtube.

Due to the sheer amount of channels, I organized them into three broad categories: use of R as statistical software, use of other statistical software, and lecture format only. I also listed each channel's content/topic, whether authors provided slides, code, additional materials online (with links), and relevant remarks.

1. Learning Statistics with R

               
Youtube channelContentSoftware Online Materials? Remarks
Mike Marin [Intro] Basic Stats in R R Yes, good materials University British Columbia
Michael Butler [Intro] to R and Stats, Modern R Yes Good intro to R + Exercises
EZLearn [Intro] Basic Stats in R R Exercises w/ solutions -
Renegade Thinking: Courtney Brown [Intro] Undergraduate Stats R Yes Good Lectures
Barton Poulson [Intro] Classical Stats, Programming & Solved Exercises R, Python, SPSS Yes Gives intro to Python, R, SPSS and launching an OLP
Ed Boone [Intro] Basic R and SAS R & SAS Yes -
Bryan Craven [Intro] Basic Stats in R R -
Lynda.com [Intro] Basics of R and Descriptives R Yes OLP
Bryan Craven [Intro] Basic Stats in R R No -
Laura Suttle (Revolution) [Intro] R tour for Beginners R No -
Phil Chan [Intro] Classical and Bio-stats R, SPSS, Eviews No -
Gordon Anthony Davis [Intro] R Programming Tutorial R No Thorough intro for beginners
Nathaniel Phillips [Intro] R Programming Tutorial R Yes Videos as a pedagogical tool for his R book
David Langer [Intro] Basics of R R No Excellent pedagogical Skills
MrClean1796 [Intro] Math, Physics and Statistics, lecture & R R No -
Brian Caffo Advanced & Bio-Stats, Reproducible Research R Yes, Coursera and GitHub Professor of Bio-statistics, Johns Hopkins Univ.
Abbass Al Sharif In-depth Machine Learning R Yes Excellent lectures and resources
James Scott Advanced Stats R Yes, and GitHub Several Course Materials on GitHub
Derek Kane Machine Learning R Yes Excellent Videos, Fourier Analysis, Time series Forecasting
DataCamp Programming, DataViz, R Markdown [free] R Yes, paid. 9$ for students -
Maria Nattestad DataViz R Personal Website Plotting in R for Biologists
Christoph Scherber Mixed, GLM, GLS, Contrasts R Yes -
Librarian Womack Time Series, DataViz, BigData R Yes, Course and .R Materials online
Jarad Niemi R Workflow, Bayesian, Statistical Inference R Yes -
Justin Esarey Bayesian, Categorical and Longitudinal Data, Machine Learning R Yes, lots and lots Political Scientist
Jeromy Anglim Research Methods R Blog:Psych & Stats, GitHub + Rmeetups and Notes on Gelman, Carlin, Stern, and Rubin
Erin Buchanan Under- & post-graduate Stats, SEM R, G*Power, Excel Yes Excellent pedagogical strategies
Richard McElreath From Basic to Advanced Bayesian Stats R and Stan Yes, lots Book lectures
edureka Data Science R, Hadoop, Python Yes, online learning plattaform R Intro w/ Hadoop [free]
Learn R R programming, stats on webiste R, Python Yes, and One R Tip A Day On website, lots of starter's code
Data School Machine Learning, Data Manipulation (dplyr) Python, R Yes, dplyr Machine Learning with Hastie & Tibshirani
Econometrics Academy Statistics (via Econometrics) R, STATA, SPSS Yes OLP, Excellent Materials and Resources
Jalayer Academy Basic Stats + Machine Learning R, Excel No Also Lectures
Michael Levy Authoring from R, Markdown, Shiny R No -
Melvin L. Machine Learning, R Programming, PCA, DataViz R, Python, Gephi No Interesting Intro for Spark
OpenIntroOrg Intro to Stats/R plus Inference, Linear Models, Bayesian R Yes, Coursera and OpenIntro Coursera Courses, Resources in SAS
Mike Lawrence Tidyverse, Wrangling & DataViz, plus Bayesian Inference R, Stan, rstan Yes, w/ Lit too And relevant repos on GitHub
 

2. Learning Statistics with other software

               
Youtube channelContentSoftware Online Materials? Remarks
Jonathan Tuke Basic Stats Matlab No -
Saiful Yusoff PLS, Intro to MaxQDA SmartPLS, MaxQDA Yes BYU
James Gaskin SEM, PLS, Cluster SPSS, AMOS, SmartPLS Yes BYU
Quantitative Specialists Basic Stats SPSS No Upbeat videos
RStatsInstitute Basic Stats SPSS No Instructor at Udemy
how2stats Basic Stats, lecture and software demonstrations SPSS Yes Complete Classical Stats
BrunelASK Basic Stats SPSS -
The Doctoral Journey Basic Stats SPSS Yes -
StatisticsLectures Basic Stats, lecture format SPSS Yes discontinued, but thorough basic stats
Andy Field Classical Stats, lecture and software demonstrations SPSS Yes, registration needed Used heavely in Social Sciences
Quinnipiac University:Biostatistics Classical Stats SPSS No -
The RMUoHP Biostatistics Basic and Bio-Stats SPSS, Excel No -
PUB708 Team Classical Statistics SPSS, MiniTab No -
Professor Ami Gates Classical Stats SPSS, Excel, StatCrunch Yes -
H. Michael Crowson Intro and Basic Stats in several Softare SPSS, STATA, AMOS, LISREAL Yes? -
Math Guy Zero Classical Stats + SEM SPSS, Excel, PLS No Lots of materials
BayesianNetworks Bayesian Statistics, SEM, Causality BayesianLab Yes -
Khan Academy Programming 101 Python Yes -
Mike's SAS Short intro to SAS, SPSS SAS, SPSS No -
Christian A. Wandeler Basic Stats PSPP No -
 

3. Lectures on statistics

               
Youtube channelContentSoftware Online Materials? Remarks
Stomp On Step 1 [Intro] Bio-Stats, Basic Lectures Yes USMLE
Khan Academy [Intro] Basic Stats, lecture format Lectures Yes -
Joseph Nystrom [Intro] Basic Stats Lectures Yes Active & unorthodox teaching
Statistics Learning Centre [Intro] Basic Stats Lectures Yes Register to access materials
Brandon Foltz [Intro] Basic Stats Lectures soon Excellent visuals
David Waldo [Intro] Probability Theory Lectures No -
Andrew Jahn [Intro] Basic Stats Lectures No FSL, AFNI and SPM [Neuro-immaging]
Professor Leonard [Intro] Stats and Maths Lectures No Excellent pedagogical skills
ProfessorSerna [Intro] Basic Stats Lectures No -
Harvard University [Intro] Thorough Introduction to Probability Theory and Statistics Lectures No In-depth
Victor Lavrenko Machine Learning, Probabilistic, Cluster, PCA, Mixture Models Lectures Yes, very complete Excellent Content, and lots of it
Jeremy Balka's Statistics Graduate-level Classical Stats, Lecture Lectures Yes, very thorough Excellent altogether, p-value vid great!
Methods Manchester Uni Discussion on a wide variety of methods, SEM Lectures Yes Methods Fair
Steve Grambow Series on Inference Lectures Yes Great Lectures on Inference [DUKE]
Statistics Corner: Terry Shaneyfelt Statistical Inference Lectures Yes from a clinical perspective
Michel van Biezen Complete Course of Stats Lectures Yes, 1, 2, 3 Thorough and complete, plus Physics and Maths
Oxford Education Bayesian statistics: a comprehensive course Lectures Yes -
Nando de Freitas Machine Learning Lectures Yes, also here and here -
Alex Smola Machine Learning Lectures Yes, slides and code -
Abu (Abulhair) Saparov Machine Learning Lectures Yes Taught by Tom Mitchell and Maria-Florina Balcan
Geoff Gordon Machine Learning, Optimization Lectures Yes -
MIT OpenCourseWare Probability Theory, Stochastic Processes Lectures Yes, here, and here -
Alexander Ihler Machine Learning Lectures Yes, along w/ many others classes -
Royal Statistical Society Important Statistical issues Lectures Yes Interesting topics
Ben Lambert Graduate and Advanced Stats Lectures No Asymptotic Behaviour of Estimators, SEM, EFA
DeepLearning TV Machine (and Deep) Learning Lectures No Excellent pedagogical skills
Mathematical Monk Machine Learning, and Probability Theory Lectures No -
Matthew McIntosh Probability Theory, Generalized Linear Models, underlying mathematics Lectures No Excellent mathematical derivations
 

Final Remarks

These collection of channels listed here are not supposed to be exhaustive. If I have neglected a youtube channel that you think should figure in this list, please let me know via the contact form below and I shall include it. Thank you very much!

postscriptum  [21/09/2016]

I am delighted with the reaction this post received on social media, which is mainly due to being published on R-bloggers (Thank you Tal Galili) As of today, it has received 450 shares and 500 likes [from both here and here].