# Tutorial

# Science Research Methods: Tutorials

## by Peter K. Dunn

TUTORIALS for quantitative research in science, engineering and health (including research design, hypothesis testing and confidence intervals in common situations) […] This book has been prepared for use with the book Scientific Research and Methodology, to be used in the course Science Research Methods at the University of the Sunshine Coast (UniSC). This course is an introduction to quantitative research methods in the scientific, engineering and health disciplines. It introduces the whole research process, from asking a research question to analysis and reporting of the data. The focus, … Read more →

# iPhylo Tutorial

## by Chen Peng and Yueer Li

This is a tutorial for the iPhylo website. […] We present the iPhylo suite (https://www.iphylo.net/), a comprehensive, automated, and interactive platform for biological and chemical taxonomic analysis. Please cite iPhlyo if it helps your research: Yueer Li#, Chen Peng#, Fei Chi, Zinuo Huang, Mengyi Yuan, Chao Jiang* (2023). The iPhylo suite: an interactive platform for building and annotating biological and chemical taxonomic … Read more →

# ECOM20001 Tutorial Questions and Suggested Solutions

## by Richard Hayes

This is an example of using the bookdown package to write a collate all the tutorial questions and answers in semester 2, 2023 in a book. The HTML output format for this example is bookdown::gitbook, set in the _output.yml file. [...] This is a sample book written in Markdown that covers the questions and suggested solutions to tutorials posted in semester 2, 2023. Each bookdown chapter contains the questions and suggested solutions for each tutorial. One of the reasons for putting this book together was to assist in your exam revision. Most of the solutions are hidden so you should ... Read more →

# Understanding Digital Information Flow via Computational Methods

## by Valerie Hase, LMU Munich

B.A. Seminar at LMU Munich, Fall 2023/2024 […] This online tutorial will accompany the seminar “Understanding Digital Information Flow via Computational Methods”. It is part of the undergraduate course “Communication Studies” (LMU, Department of Media and Communication) and takes place Friday 10 am to 2pm in the CIP pool, Akademiestr. 7. You will find all necessary information on the seminar’s structure, important dates and assessments/evaluations via Moodle. Please carefully consider the syllabus when deciding whether to participate in this seminar. This tutorial will introduce you to two … Read more →

# Mit Emma durch den Daten-Dschungel

## by Daniel Schumann & Oliver Böhm-Kasper

Begleitdokument zur Selbstlerneinheit “Mit Emma durch Daten-Dschungel” […] Dieses Tutorial soll Dich bei der Bearbeitung des Selbstlernkurses “Mit Emma durch den Daten-Dschungel” unterstützen. Du hast mit Emma bislang verschiedene Schritte auf ihrem Weg zur empirischen Abschlussarbeit erlebt. Nun kannst Du gemeinsam mit Emma das Auswertungsprogramm “R / RStudio” kennenlernen. (R ist das eigentliche Auswertungsprogramm; RStudio ist eine nutzerfreundliche Entwicklungsumgebung zur einfacheren Bedienung des Programms R.) Dieses Dokument soll Dir helfen, die einzelnen Schritte der … Read more →

# An Introduction to R for Research

## by Ramzi W. Nahhas

This text was written to provide Wright State University MPH students an introduction to the R programming language for use in research. […] This online book was written to provide Wright State University MPH students an introduction to the R programming language for use in research. The datasets used in this text are not being made publicly available. If you are using this material as part of a Wright State University course or tutorial, datasets will be provided to you by the instructor or in your learning management system. If you have any comments or suggestions, feel free to contact … Read more →

# Spatial transcriptomics data analysis: theory and practice

## by Eleftherios Zormpas, Dr Simon J. Cockell

This book will guide you through the practical steps of the in-person tutorial IP2 for the ISMB/ECCB 2023 conference in Lyon named: Spatial transcriptomics data analysis: theory and practice. […] This book will guide you through the practical steps of the in-person tutorial IP2 for the ISMB/ECCB 2023 conference in Lyon named: “Spatial transcriptomics data analysis: theory and practice”. Recent technological advances have led to the application of RNA Sequencing in situ. This allows for whole-transcriptome characterisation, at approaching single-cell resolution, while retaining the spatial … Read more →

# The Epidemiologist R Handbook

## by the handbook team

The Epi R Handbook is a R reference manual for applied epidemiology and public health. […] Usage: This handbook has been used over 1 million times by 450,000 people around the world. Objective: Serve as a quick R code reference manual (online and offline) with task-centered examples that address common epidemiological problems. Are you just starting with R? Try our free interactive tutorials or synchronous, virtual intro course used by US CDC, WHO, and 75+ other health agencies and Field Epi Training Programs worldwide. Languages: French (Français), Spanish (Español), Vietnamese (Tiếng … Read more →

# Data Donations - Tutorial Automated Content Analysis

## by Valerie Hase, LMU Munich

Data Donations - Tutorial Automated Content Analysis, LMU, Spring 2023 […] This online tutorial will accompany the seminar “News on and for Social Media”. It is part of the B.A. “Communication Research” (LMU, Spring 2023). In short, it supports the group using automated content analysis for analyzing data donations. This tutorial will introduce you to two main aspects: You are expected to work through the content of these tutorials before each of our regular sessions so we can use in-person meetings to discuss questions/test your new knowledge via exercises. Each tutorial includes First of … Read more →

# Simulation Models of Cultural Evolution in R

## by Alex Mesoudi

This tutorial shows how to create very simple simulation or agent-based models of cultural evolution in R [...] This tutorial shows how to create very simple simulation or agent-based models of cultural evolution in R (R Core Team 2021). Currently these are: Each model is contained in a separate RMarkdown (Rmd) file. You can either (i) download each of these Rmd files from https://github.com/amesoudi/cultural_evolution_ABM_tutorial then open them in RStudio or another IDE, executing the code as you read the explanatory text, or (ii) read the online version of the tutorial at ... Read more →

# R Bootcamp

## by Yun Dai

This is the ebook version of the four-week online R Bootcamp. The HTML output format for this example is bookdown::gitbook, set in the _output.yml file. [...] Hello! This is the ebook version of the four-week online R Bootcamp. This website is not an exact replica of the video tutorials, but it offers links to resources and more recent updates compared to the videos. Additionally, the written format and organized table of contents are designed to help users find the information needed quickly. In the past, some have found this feature useful. The Bootcamp is designed for newcomers to R ... Read more →

# Multiple Membership Models: A tutorial

## by Laura Lambert

This is work done for a final project at JMU for the PSYC836 Hierarchical Linear Models course taught by Dr. Dena Pastor. It is intended to give a brief introduction to multiple membership multilevel models as well as a walkthrough of how to run such a model using the R2MLwiN package to interface with the MLwiN software. […] This is a fictional scenario and data set designed for the sole purpose of illustrating the coding and interpretation of multiple membership models using the R2MLwiN package. These data were simulated by myself, and were designed to loosely resemble a population of … Read more →

# Machine Learning-based Causal Inference Tutorial

## by Golub Capital Social Impact Lab

This is a tutorial on machine learning-based causal inference. […] This tutorial will introduce key concepts in machine learning-based causal inference. It’s an ongoing project and new chapters will be uploaded as we finish them. Topics currently covered: Please note that this is currently a living document. If you find any issues, please feel free to contact Undral Byambadalai at undralb@stanford.edu. The “changelog” below will keep track of major updates and additions. We’ll illustrate key concepts using snippets of R code. Each chapter in this tutorial is self-contained. You can download … Read more →

# SAS Tutorial

## by Hao Sun

SAS Tutorial … Read more →

# Bayesian Linear Regression Tutorial

## by Xiang Chen, Valentina Arputhasamy, Daniel Zhou, Sudipto Banerjee

This is a first tutorial for Bayesian Linear Regression assembled in book form. […] This is a tutorial for Bayesian Linear Regression assembled in book … Read more →

# Statistical Inference

## by Michael Foley

Notes cobbled together from books, online classes, etc. to be used as quick reference for common work projects. […] These are notes from books, classes, tutorials, vignettes, etc. They contain mistakes, are poorly organized, and are sloppy on fundamentals. They should improve over time, but that’s all I can say for it. Use at your own risk. The focus of this handbook is statistical inference, including population estimates, group comparisons, and regression modeling. Not included here: probability, supervised ML, unsupervised ML, text mining, time series, survey analysis, or survival … Read more →

# 🃏 Probability I

## by Dr. Daniel Flores Agreda (based on the Lecture by Prof. Davide La Vecchia)

Course Materials […] Hello and Welcome to this introductory Lecture in Probability! These Course Notes are a complement to the Lecture Probability I. The Lecture is divided in the following Chapters, and each Chapter contains several themes. The Lectures will take place in the room MR280 on Thursday from 12h15 to 14h00. For those students who cannot attend the lectures, a recording will be available on Mediaserver. Seminars will take place on Thursday from 16h15 to 18h00 in the room MS130. The seminars are not recorded. Every two week (starting from the third one), tutorials will take place … Read more →

# Bayesian Linear Regression

## by Xiang Chen, Dr. Sudipto Banerjee

This is a tutorial for Bayesian Linear Regressione. […] Theorem 1.1 (Bayes’ theorem) For events (A, B) and (P(B) \neq 0), we have [P(A\mid B) = \frac{P(B \mid A) P(A)}{P(B)}] We denote (U) as unknown parameters and (K) as known parameters. We call (P(U)) prior and (P(K|U)) likelihood. The Bayes’ theorem gives us the posterior distribution of unknown parameters given the known parameters [ P(U \mid K) \propto P(U) \cdot P(K \mid U)] Let (K = \left{y_{n \times 1}, X_{n \times p} \right}) and assume (y \sim N\left( X \beta, \sigma^{2} V\right)), where (V) is known and … Read more →

# Cross-Platform Journalism: News use, content, and effects

## by Valerie Hase, LMU Munich

Cross-Platform Journalism - B.A. Seminar at LMU Munich, Fall 2022/2023 […] This online tutorial will accompany the seminar “Cross-Platform Journalism: News use, content, and effects”. It is part of the undergraduate course “Communication Studies” (LMU, Department of Media and Communication). At the moment, the course is expected to take place via in-person meetings every Tuesday 08:00-10:00 am in room B109, Edmund-Rumpler-Strasse 13. Please note that this may change in light of COVID-19 developments. You will find all necessary information on the seminar’s structure, important dates and … Read more →

# R for marketing students

## by Samuel Franssens

R tutorial for marketing students […] In this tutorial, we will explore R as a tool to analyse and visualise data. R is a statistical programming language that has rapidly gained popularity in many scientific fields. The main difference between R and other statistical software like SPSS is that R has no graphical user interface. There are no buttons to click. R is run entirely by typing commands into a text interface. This may seem daunting, but hopefully by the end of this tutorial you will see how R can help you to do better statistical analysis. So why are we using R and not one of the … Read more →

# STAT101 Tutorials

## by speedyjiang

STAT101 Tutorials […] Weekly tutorial exercises (starting in Week 1) are assigned from the required course textbook, Lock, Lock, Lock Morgan, Lock and Lock, Statistics: Unlocking the Power of Data, 2nd Edition, (2017) Wiley. You can find details on where to source the textbook in the Course Information section. You do not need to get the textbook exercises finished or correct during the tutorial, we just want you to give them your best attempt. However, mastering these concepts is strongly recommended in preparation for the final exam. Your attempts at the textbook exercises will not be … Read more →

# An Introduction to ggplot2

## by Ozancan Ozdemir

A ggplot2 Tutorial […] Hi! Data Visualization is one of the important steps of the data analysis process. It is actually not only part of the data analysis, but also can be considered as an art. R Programming language provides a powerful visualization package to us, ggplot2. This book aims to show how you can make a well-known statistical plots by using ggplot2, and also how you can improve or customize them. The book is created by the lab notes of statistical computing (STAT 291-STAT 292) of Ozancan Ozdemir. For your opinions and suggestions, please send me an e-mail to … Read more →

# Methods in (Skene & Kenward, 2010)

## by Dylan Dijk

This is a minimal example of using the bookdown package to write a book. The HTML output format for this example is bookdown::bs4_book, set in the _output.yml file. [...] This tutorial aims to show how methods described in the two papers by Simon S. Skene and Michael G. Kenward1,2 (paper I and paper II) can be applied in R. In these papers, it is assumed that the data can be represented by a multivariate Gaussian linear model. The model has the following form: \[\begin{equation} y_i \sim N(X_i \beta;\Sigma_i ), \quad i =1, \dots,n \tag{1.1} \end{equation}\] where \(y_i\) \((T_i \times ... Read more →

# Model Based Sampling with EMC2 - Extended Models of Choice

## by Reilly Innes, Niek Stevenson, Russell Boag, Andrew Heathcote

This bookdown provides a tutorial on how to use EMC2. […] This project provides a tutorial for learning about cognitive models, namely evidence accumulation models (EAMs), their implementation and their applications. The tutorial was prepared by Andrew Heathcote, Dora Matzke, Russell Boag, Niek Stevenson and Reilly Innes. The GitHub repository for this project can be found here. The accompanying samples for the code provided here can be found at here. Throughout this guide, we’ll use some complex terminology for different aspects of modelling. We know that models exist, and in particular, … Read more →

# AI4PH2022.knit

## by Yuan Tian, Ph.D(c)

Welcome to AI4PH Summer Institute 2022. […] The material is prepared for the tutorial session of the AI4PH event 2022. Please do not cite or distribute without author’s … Read more →

# Reproducible Science for Busy Researchers: How to Save Time using Literate Programming

## by Dr. Andrew P. Lapointe

This is a minimal example of using the bookdown package to write a book. The output format for this example is bookdown::gitbook. […] Signe recommended students run a live tutorial in swirl Google Analytics https://benmarwick.github.io/bookdown-ort/mods.html#google-analytics These resources are not relevant for students but they are to me. To render the book used the following code, you must do this before knitting the GitBook (webpage) The _output.yml contains the header arguments. I would but them here so its cleaner and easier to read the code. Is there a way I can have matlab code … Read more →

# _main.knit

## by Cesar Nillaga, Milo Weller, Sophie Moore

This tutorial investigates the methods of hieararchial clustering. We investigated the usage of heirarchial clustering and how it could be applied to targeting groups using the spotify data. […] This tutorial will investigate what cluster analysis is and how it can be used to identify or predict groups with data. Our group focused on spotify data and we tried to group genres based on song characteristics. Later in this tutorial we will be using a dataset containing 15 different genres and through analysis we will see if we group similar genres together. Cluster analysis is a technique in … Read more →

# Modern Statistical Methods for Psychology

## by Mine Çetinkaya-Rundel and Johanna Hardin, tuned by Gregory Cox

This is the website for Modern Statistical Methods for Psychology, a modified version of Introduction to Modern Statistics, First Edition by Mine Çetinkaya-Rundel and Johanna Hardin, as modified by Gregory Cox. The original Introduction to Modern Statistics is a textbook from the OpenIntro project. — Version date of this modification: May 24, 2022. The original version of the Introduction to Modern Statistics textbook and its supplements, including slides, labs, and interactive tutorials, may be downloaded for free atopenintro.org/book/ims. This textbook is itself a derivative of OpenIntro … Read more →

# A Practical Guide to Sensitivity Analysis for Causal Effects in the Presence of Non-Ignorable Loss to Follow-Up

## by Aleya Khalifa and Gloria HJ Graf

This is a minimal example of using the bookdown package to write a book. The HTML output format for this example is bookdown::gitbook, set in the _output.yml file. [...] Welcome! This tutorial provides a roadmap for sensitivity analyses to assess the impact of loss to follow-up on causal effect estimates. In particular, we introduce and implement a multiple-imputation-based pattern-mixture approach to MNAR mechanisms based on previous work by Leurent et al. (2018 Pharmacoeconomics). This tutorial is intended for any public health researcher who is seeking an easily implemented, ... Read more →

# R for marketing students

## by KU Leuven Marketing department

KULeuven R tutorial for marketing students […] In this tutorial, we will explore R as a tool to analyse and visualise data. R is a statistical programming language that has rapidly gained popularity in many scientific fields. The main difference between R and other statistical software like SPSS is that R has no graphical user interface. There are no buttons to click. R is run entirely by typing commands into a text interface. This may seem daunting, but hopefully by the end of this tutorial you will see how R can help you to do better statistical analysis. So why are we using R and not one … Read more →

# Probability

## by Michael Foley

Notes cobbled together from books, online classes, etc. to be used as quick reference for common work projects. […] These are notes from books, classes, tutorials, vignettes, etc. They contain mistakes, are poorly organized, and are sloppy on fundamentals. They should improve over time, but that’s all I can say for it. Use at your own risk. The focus of this handbook is probability, including random variables and probability distributions. Not included here: statistics, machine learning, text mining, survey analysis, or survival analysis. These subjects frequently arise at work, but are … Read more →

# Bookdown Template

## by Rethink Priorities

Bookdown Template […] This book is a bookdown template to be used for various projects of the Rethink Priorities survey team. The main goal of this book is to serve as a skeleton project that can be copied and used in other projects. Additionally, it contains some chapters that serve as tutorials for different features of this bookdown format. Please add yourself to the list below to acknowledge your contributions. Willem Sleegers: willem@rethinkpriorities.org David Reinstein: dreinstein@rethinkpriorities.org … Read more →

# An(other) introduction to R

## by Felix Lennert

This is a gentle introduction to R and the basic usage of some tidyverse packages (dplyr, tidyr, ggplot2, forcats, stringr) for data manipulation and visualization. […] Dear student, in the following, you will receive a gentle introduction to R and how you can use it to work with data. This tutorial was heavily inspired by Richard Cotton’s “Learning R” (Cotton 2013) and Hadley Wickham’s and Garrett Grolemund’s “R for Data Science” (abbreviated with R4DS). The latter can be found online (Wickham and Grolemund 2016). We will not immediately start out with the packages from the tidyverse … Read more →

# Text as Data Methods in R - Applications for Automated Analyses of News Content

## by Valerie Hase, IKMZ, University of Zurich

Text as Data Methods in R - M.A. Seminar at IKMZ, HS 2021 […] This online tutorial will accompany the seminar “Text as Data Methods in R - Applications for Automated Analyses of News Content”. It is part of the M.A. “Internet & Society” (IKMZ, University of Zurich, HS2021). At the moment, the course is expected to take place via in-person meetings every Tuesday 10:15-12 am in room BIN-1-D.25. Please note that this may change in light of new COVID-19 developments. You will find all necessary information on the seminar’s structure, important dates and assessments/evaluations via OLAT. Please … Read more →

# Step by Step I: Linear Models

## by Sérgio Moreira

My Coding Index assembles and organizes in one place all the relevant code and online resources I have been using to teach RStudio and in my professional practice. This file is a working document and will be regularly updated with reviews and new contents. […] Step by Step I assembles in one place the tutorials I have been using to teach and apply to practice simple, multiple and hierarchical linear models. This file is a working document and will be regularly updated with reviews and new contents. My name is Sérgio. I have a PhD in Social Psychology, I am a consultant on social issues in … Read more →

# BS2001: Physiology

## by Curated by: Kevin Fo

This a website built for studying BS2002: Physiology […] This is a bookdown site generated for the NTU SBS course BS2001: Physiology (a core module for BS students). More information about this website will be shown in the following sections: At the time of your visit, weeks, months, or even years may have passed. Hence, the material presented on this website may no longer be up-to-date for future iterations of this course. Furthermore, this bookdown site is not a substitute for skipping lectures and / or tutorials. The curator encourages current and prospective students to be responsible … Read more →

# Forschungsseminar: Text as data

## by Valerie Hase, IKMZ, Universität Zürich

Codes and notes for the text as data seminar at IKMZ, HS 2020/FS201 […] Dieses Tutorial begleitet das Forschungsseminar “Text as Data - Automatisierte Inhaltsanalyse in der Kommunikationswissenschaft” (IKMZ, Universität Zürich, HS2020). Alle nötigen Informationen zum Ablauf des Seminars, Prüfungsleistungen und Aufnahmen der Seminarsitzungen finden Sie auf OLAT. Dieses Tutorial hat zwei zentrale Ziele: Struktur der R-Tutorials Sie finden hier die jeweiligen Tutorials, die Sie bis zur jeweiligen Sitzung im Plenum durcharbeiten. Die Sitzungen selbst werden dann genutzt, um offene Fragen und … Read more →

# Franchise Hockey Manager 6 Saves in R

## by Canadice

Franchise Hockey Manager 6 Saves in R […] This tutorial hopes to teach you how to use R to parse and aggregate multiple saves from Franchise Hockey Manager 6, for instance when running multiple tests on the same season of Simulation Hockey League. It has been updated to show the teams and Casino Lines for S61. Two things are needed from FHM for this tutorial to work. A tldr is found in chapter 4. This chapter only contains all the code that you need to … Read more →

# BIONB 2210 Summer 2021 Computer Labs

## by Dena J. Clink

This is the location for all of the tutorials associated with the behaviouR R package. […] You have reached the location for all of the tutorials for the computer labs for Summer 2021. We will be completing all assignments using Rstudio Cloud (www.rstudio.cloud). Please see the link on Canvas for details on how to setup your RStudio Cloud account. Note: If you have never used R before I highly recommend that you check out the primers here: https://rstudio.cloud/learn/primers. You can navigate using the tabs at the left and/or the … Read more →

# 2021 REU Data Science Training

## by Haoqi Wang

2021 REU Data Science Training […] Knowledge Gained: R, data wrangling, data visualization Main materials: Other resources Software: R Weekly Time-Commitment: 3-6 hrs of independent asynchronous work by students supplemented with ~1-3 hours of grad student led synchronous support. Asynchronous work: working through video tutorials Synchronous … Read more →

# The Social Life of Neighborhoods: Data Preparation & Mapping Tutorials

## by Professor Forrest Stuart, TA: Francine Stephens

This is a website with tutorials for the Social Life of Neighborhoods offered in SOC 176/276. […] The following is a series of tutorials specifically designed for The Social Life of Neighborhoods (SOC 176/SOC 276/AFRICAAM 76B/CSRE 176B/URBANST 179) course. The course assignments and final story map require collecting and analyzing information about neighborhoods and other urban spaces. In the tutorials, you will be introduced to tools that will allow you to gather, process, and visualize data so that you can complete the assignments and create your own story map. No prior experience or … Read more →

# A Crash Course in Geographic Information Systems (GIS) using R

## by Michael Branion-Calles

A Crash Course in Geographic Information Systems (GIS) using R […] There is an assumption of some previous experience in R with this tutorial. If you have not used R before I would start with Chapter 1 of the free, and excellent textbook R for Data Science. The GIS operations in R from the sf package are designed to integrate well with the tidyverse suite of R packages. We will make use of some basic functionality from the dplyr package and will be using pipes (%>%) to sequence multiple operations. If you are unfamiliar with dplyr and pipes I would go through the base vignette before … Read more →

# R Notes for QRM

## by Shih-Sheng Chang

R Notes for QRM […] This is a note based on the book “Quantitative Risk Management: Concepts, Techniques and Tools” by Alexander J. McNeil, Rüdiger Frey and Paul Embrechts, published by Princeton University Press in 2015 (revised 2nd edition, 1st edition 2005) and the book “The Quantitative Risk Management Exercise Book” by Marius Hofert and Rüdiger Frey and Alexander J. McNeil, published by Princeton University Press in 2020. The note contains theoretical definitions and R codes based on QRM Tutorial by Marius … Read more →

# Tutorial

## by Golub Capital Social Impact Lab

This is a tutorial on machine learning-based causal inference. […] This tutorial will introduce key concepts in machine learning-based causal inference. It’s an ongoing project and new chapters will be uploaded as we finish them. A tentative list of topics that will be covered: Please note that this is currently a living document. Chapters marked as “beta” may change substantially and are in most need of feedback. If you find any issues, please feel free to contact Vitor Hadad at vitorh@stanford.edu. The “changelog” below will keep track of major updates and additions. We’ll illustrate key … Read more →

# Policy Learning I - Binary treatment

## by Golub Capital Social Impact Lab

A short tutorial for machine-learning based causal inference. […] This tutorial will walk you through common statistical tools used in the lab. If you’re self-studying, here’s a minimal recommended study plan for newcomers: If you are working on a particular project, you can jump into a relevant section. Any pre-requisites are listed at the beginning of each … Read more →

# STAB Tutorials

## by UW STAB Working Group

Tutorials for the UW STAB working group […] This site is currently in development. It will eventually contain tutorials related to the STAB working group at the University of Washington. This site was built using … Read more →

# Data Science for Human-Centered Product Design

## by Travis Kassab

Data Science for Human-Centered Product Design […] This is a data science tutorial with seven open-source projects that show how statistics and machine learning can be applied to user survey data. The purpose is not to prescribe techniques, but to demonstrate the use of data science in the context of product design. I’ve compiled what I know on the topic, and hope readers adopt some of these techniques and use them in concert with qualitative research and entrepreneurial thinking to build better products. Let’s quickly preview the seven different use-cases. First, we must develop an … Read more →

# Analyzing and visualizing fiber photometry data with fluoR

## by Andrew Tamalunas

A living bookdown document focused on exploration, visualization, and analysis of neurobiological time series data - especially in the context of testing behavioral hypothesis. […] Analyzing and visualizing fiber photometry data with fluoR is a continuously updated book of tutorials and background information for analyzing and visualizing time series data from behavioral experiments. The fluoR R package is the successor to the GCalcium package, which I initially wrote to help ensure that my fiber photometry data analyses were accurate, consistent, and transparent. Both R packages and this … Read more →

# Dispersing or clustering: Spatial Pattern Analysis for Public Use and Taxi’s Rapid Charging Facilities in London, UK

## by Student Number: 19175131

This is a tutorial book with R Markdown for CASA0005 final coursework containing code and instruction of the whole analyzing process. Course name: CASA0005 Geographic Information Systems and Science Program: MSc Spatial Data Science and Visualisation Department: Centre for Advanced Spatial Analysis GitHub repository: https://github.com/LingruFeng/GIS_assessment Rpubs link: https://rpubs.com/Lingru/GIS_assessment … Read more →

# A Minimal rTorch Book

## by Alfonso R. Reyes

This is a minimal tutorial about using the rTorch package to have fun while doing machine learning. This book was written with bookdown. […] Last update: Sun Oct 25 12:05:18 2020 -0500 (79503f6ee) You need couple of things to get rTorch working: Install Python Anaconda. Preferably, for 64-bits, and above Python 3.6+. I have successfully tested Anaconda under four different operating systems: Windows (Win10 and Windows Server 2008); macOS (Sierra, Mojave and Catalina); Linux (Debian, Fedora and Ubuntu); and lastly, Solaris 10. All these tests are required by CRAN. Install R, Rtools and … Read more →

# Basic R Guide for NSC Statistics

## by Deanna Li

This is an R guide for statistics course at NSC. […] This guide’s primary focus is on Basic R. When graphics are involved, command functions in both Basic R and a package called ggplot2 will be shown. Graph enhancements will be kept to a minimum. Although there are R packages that may do the same or better job than Basic R, this tutorial will not delve into those packages. Exploring other packages will be left for the student to look into, if the student so wishes. Datasets will be taken mostly from those built into R. Since this is mainly a tutorial on the R commands necessary to do … Read more →

# Integration and harmonization of trait data from plant individuals across heterogeneous sources

## by Tim P. Lenters, Andrew Henderson, Caroline M. Dracxler, Guilherme A. Elias, Suzanne Mogue, Thomas L.P. Couvreur & W. Daniel Kissling

Integration and harmonization of trait data from plant individuals across heterogeneous sources […] This tutorial gives an indepth explanation of how to use and implement the different aspects of the workflow as described in Lenters et al., (submitted) It consists of different … Read more →

# Text as Data para Ciências Sociais

## by Davi Moreira

Compilação de métodos e técnicas para análise automatizada de conteúdo […] A partir da produção de material para o curso Text as Data: análise automatizada de conteúdo que ministrei no MQ-UFMG em 2019 e no artigo que publiquei em coautoria com Maurício Izumi (Izumi and Moreira 2018), esse livro tem como propósito difundir nas ciências sociais e humanidades técnicas e métodos de análise automatizada de conteúdo usando a linguagem R. O principal objetivo do livro é ser tutorial prático de uso e aplicação de técnicas e métodos de análise automatizada de conteúdo na língua portuguesa através da … Read more →

# behaviouR: R package and tutorials for teaching of fundamental concepts in behavior and ecology

## by Dena J. Clink

This is the location for all of the tutorials associated with the behaviouR R package. […] To get started you should download the package from Github using the following code. Note: If you have never used R before I highly recommend that you check out the primers here: https://rstudio.cloud/learn/primers. You can navigate using the tabs at the left and/or the … Read more →

# My Data Science Notes

## by Michael Foley

This is a compendium of notes from classes, tutorials, etc. that I reference from time to time. […] These notes are pulled from various classes, tutorials, books, etc. and are intended for my own consumption. If you are finding this on the internet, I hope it is useful to you, but you should know that I am just a student and there’s a good chance whatever you’re reading here is … Read more →

# Exercises for ‘Introduction to The New Statistics’

## by Peter Baumgartner

This website is a companion book for Introduction to the New Statistics (abbreviated itns). It offers interactive exercises developed mostly in H5P but also with learnr and shiny. It also contains an R tutorial for the end-of-chapter exercises of itns. […] This website is an (inoffical) companion book for Introduction to the New Statistics (abbreviated itns). It offers GitHub resources of this book can be found in two places: I have built the interactive exercises in this book with H5P.org. H5P stands for HTML5 Package, a free and open-source content collaboration framework based on … Read more →

# BioNBB 2210 Summer 2020 Computer Labs

## by Dena J. Clink

This is the location for all of the tutorials for our Intro to Behavior Computer Labs. […] You have reached the location for all of the tutorials for the computer labs for Summer 2020. We will be completing all assignments using Rstudio Cloud (www.rstudio.cloud). Please see the link on Canvas for details on how to setup your RStudio Cloud account. Note: If you have never used R before I highly recommend that you check out the primers here: https://rstudio.cloud/learn/primers. You can navigate using the tabs at the left and/or the … Read more →

# R Programming Tutorial

## by Thieu Nguyen

This is a minimal example of using the bookdown package to write a book. The output format for this example is bookdown::gitbook. […] R is a programming language and software environment for statistical analysis, graphics representation and reporting. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows and Mac. This programming language … Read more →

# Handbook for Building and Teaching Online Courses

## by Martin Schedlbauer Khoury College of Computer Sciences Northeastern University Boston (USA)

Notes and tutorials on building online courses. […] This handbook is still in draft form and many chapters are unfinished or in a “notes state”. Chapters, sections, and practices are filled in as need arises. This book summarizes my experiences building and teaching online courses at Northeastern University’s Khoury College of Computer Sciences. I wrote this handbook for faculty new to teaching online and new to building courses for online delivery. The writing of this handbook was accelerated when the COVID-19 pandemic forced all classes to go into an online or remote instruction mode. It … Read more →

# The jamovi quickstart guide

## by Jonas Rafi

The jamovi quickstart guide features a collection of non-technical tutorials on how to conduct common operations in jamovi. This includes how to conduct independent samples t-test, paired samples t-test, one sample t-test, ANOVA, repeated measures ANOVA, factorial ANOVA, mixed ANOVA, linear regression, and logistic regression. Additionally, the tutorials cover the use of csv files, wide data format, and setting the data type in jamovi. Read more →

# Panduan Lengkap Analisis Statistika Menggunakan R Commander

## by Mohammad Rosidi

Buku yang memberikan tutorial statistika menggunakan R-Commander, sebuah general user interface (GUI) untuk melakukan analisis dan membuat model statistika. […] … Read more →

# Sabeis - Sala Aberta de Inteligência em Saúde

## by Felipe Ferré

Wiki do SABEIS - PCDT. […] Bem vindo ao tutorial do SABEIS - PCDT. Utilize o menu ao lado para … Read more →

# Introducción a R y SIG

## by Paúl Bravo L. & Francisco Salgado C.

Introducción a R y SIG […] En esta guía tutorial, presentamos los conceptos y herramientas clave de R y su relación con los Sistemas de Información Geográfica. Articulo “Teach yourself programming in ten years” (Peter Norvig): http://norvig.com/21-days.html A Sufficient Introduction to R: https://dereksonderegger.github.io/570L/A_Sufficient_Introduction_to_R.pdf Introducción a R basada en las lecciones del paquete Swirl. Sean Kross, Nick Carchedi, Bill Bauer, Gina Grdina, Filip Schouwenaars, Wush Wu. R para principiantes: https://cran.r-project.org/doc/contrib/rdebuts_es.pdf RPubs (Daniela … Read more →

# Make money with machine learning

## by Siraj Raval, revisited by Kim NOËL

This is a minimal example of using the bookdown package to write a book. The output format for this example is bookdown::gitbook. […] This book is the personnal transcription of the course provided by Siraj Raval. A drama related to content copyright stained for Raval during this course, and many students including me were disturbed. This event swelled a lot and the motivation to progress in this course was affected. So I decided to propose a version with more explanations and details. I will provide a list of tutorials to follow in order to complete this course. This is a book written in … Read more →

# AWS Tutorial

## by Bingwei Liu

This is a minimal example of using the bookdown package to write a book. The output format for this example is bookdown::gitbook. … Read more →

# An R Exercise in Data Collection, Cleaning, and Merging U.S. Census Data

## by Sean Conner

An R Exercise in Data Collection, Cleaning, and Merging U.S. Census Data […] This document is intended as a follow-along tutorial for learning how to perform data collection and cleaning with R. To the best of my ability, I have tried to make this illustrative of real data and real tasks that anyone from a social science student to a county government official might actually encounter. To that end, I am building upon actual projects that I have worked on as a graduate research assistant to convey this information. For context, previously, I conducted a Mississippi case study of how indoor … Read more →

# Dissertating with RMarkdown and Bookdown

## by thea_knowles

A preliminary tutorial led by Thea Knowles for the R-Ladies #LdnOnt workshop series Last updated: … Read more →

# Predictive Soil Mapping with R

## by Tomislav Hengl and Robert A. MacMillan

Predictive Soil Mapping aims to produce the most accurate, most objective, and most usable maps of soil variables by using state-of-the-art Statistical and Machine Learning methods. This books explains how to implement common soil mapping procedures within the R programming language. […] This is the online version of the Open Access book: Predictive Soil Mapping with R. Pull requests and general comments are welcome. These materials are based on technical tutorials initially developed by the ISRIC’s Global Soil Information Facilities (GSIF) development team over the period 2014–2017. This book is … Read more →

# Predictive Soil Mapping with R

## by Tomislav Hengl and Robert A. MacMillan

Predictive Soil Mapping aims to produce the most accurate, most objective, and most usable maps of soil variables by using state-of-the-art Statistical and Machine Learning methods. This books explains how to implement common soil mapping procedures within the R programming language. […] This is the online version of the Open Access book: Predictive Soil Mapping with R. Pull requests and general comments are welcome. These materials are based on technical tutorials initially developed by the ISRIC’s Global Soil Information Facilities (GSIF) development team over the period 2014–2017. This book is … Read more →

# Learning statistics with R: A tutorial for psychology students and other beginners. (Version 0.6.1)

## by DJ Navarro

Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing ﬁrst, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, … Read more →

# POSEIDON tutorial

## by Ernesto Carrella

This is a basic tutorial on how to use POSEIDON and set it up to explore basic fishery problems. I try to cover everything that does not require changing any of the Java code […] This is a simple tutorial on using POSEIDON, a fishery agent-based model. You can read more about this project by reading its main paper or looking at the code repository. This guide will not explain or require any analysis of the java code. I try here to simply show what can be done by just using the graphical user interface and basic text … Read more →

# Introducción a la Computación con GPUs usando R

## by Ronald Gualán Saavedra

Revisión de conceptos clave sobre la computación GPGPU, y algunos ejemplos simples de uso de librerías aceleradas por GPU […] Las GPU (Graphics Processing Units; Unidades de Procesamiento de Gráficos) son unidades de procesamiento diseñadas originalmente para procesar gráficos en una computadora rápidamente. Esto se hace teniendo una gran cantidad de unidades de procesamiento simples para cálculos masivamente paralelos. La idea de la computación de propósito general en GPU (GPGPU: general purpose GPU computing) es explotar esta capacidad para el cálculo general. En este tutorial se revisará … Read more →

# useR! Machine Learning Tutorial

## by Erin LeDell

useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive. […] useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive This tutorial contains training modules for six popular supervised machine learning methods: Here are some practical, related topics we will cover for each algorithm: Instructions for how to install the necessary software for this tutorial is available here. Data for the tutorial can be downloaded… Certain algorithms don’t scale well when there are millions of features. For example, decision trees require computing some sort of metric (to determine the splits) on all … Read more →

# R bookdownplus Textbook

## by Peng Zhao

A tutorial to R bookdownplus, an extension of R bookdown package. This books shows helps you write academic journal articles, guitar books, chemical equations, mails, calendars, and diaries, on the basis of R bookdown. […] A book titled R bookdownplus Textbook is surely talking about ‘bookdownplus’ (Zhao 2017b), but let’s start with ‘bookdown’ (Xie 2016). ‘bookdown’ is a software package for writing books or documents based on R language (R Core Team 2016) and Markdown syntax. It is something like Microsoft Word, but more elegant, more powerful, and … Read more →

# Data Science in Educational Research

## by Joshua M. Rosenberg

This is an introduction and tutorial for data science in educational research. … Read more →

# Shiny Tutorial

## by Weicheng Zhu

This is a shiny tutorial. […] Some basic knowlege about the R lanuage is requred. It would be helpful if you have some basic knowlege about HTML, CSS and javascript, but they are not … Read more →