# Textbook

# Data Science for All

## by Kristopher Pruitt

Data Science for All […] This textbook is currently in DRAFT form and will be updated frequently. The objective of this textbook is to provide an approachable introduction to the knowledge, skills, and abilities of modern data scientists. Data-driven problem solving need not be restricted to the realm of advanced mathematics or expert computer programming. Data science can and should be practiced by all. In this text, we unveil the methods and tools applied by data scientists to solve real-world problems in a variety of domains. However, the content is accessible for anyone with the … Read more →

# 381M Course Bookdown

## by Josephine Lukito

This is a textbook for the course J381M at UT-Austin. […] Welcome to the J381M Textbook! In this course, we will learn how to use R for Computational Communication Research and Data Science, focusing on skills such as data wrangling, basic statistics, data visualization, data collection, NLP, network analysis, and machine learning. This is a survey course that is meant to give you a taste of data science. In truth, many of these topics are rich enough to warrant full courses. This textbook is best paired with the J381M course materials, including lectures, readings, and course assignments. … Read more →

# The Data Preparation Journey

## by Martin Monkman

Before you can analyze your data, you need to ensure that it is clean and tidy. […] Welcome to The Data Preparation Journey: Finding Your Way With R, a forthcoming book published with CRC Press as part of The Data Science Series. This is a work-in-progress; the most recent update is 2023-09-18. It is routinely noted that the Pareto principle applies to data science—80% of one’s time is spent on data collection and preparation, and the remaining 20% on the “fun stuff” like modeling, data visualization, and communication. There is no shortage of material—textbooks, journal articles, blog … Read more →

# Economics 395: Forecasting

## by Jaya Jha

Economics 395: Forecasting […] This resource is a compilation of Dr. Jaya Jha’s notes and code for Economics 395: Economic Forecasting. This course uses Introduction to Time Series Analysis and Forecasting as the primary textbook.1 The code sections for this class use the same data and visualizations from Introduction to Time Series Analysis and Forecasting, but not the methods.2 The methods used are from Forecasting: Principles and Practice by Rob J. Hyndman and George Athanasopoulos.3 Montgomery, Jennings, and Kulahci, Introduction to Time Series Analysis and Forecasting.↩︎ Montgomery, … Read more →

# Surrogates

## by Robert B. Gramacy

Surrogates: a new graduate level textbook on topics lying at the interface between machine learning, spatial statistics, computer simulation, meta-modeling (i.e., emulation), and design of experiments. Gaussian process emphasis facilitates flexible nonparametric and nonlinear modeling, with applications to uncertainty quantification, sensitivity analysis, calibration of computer models to field data, sequential design and (blackbox) optimization under uncertainty. Presentation targets numerically competent scientists in the engineering, physical, and biological sciences. Treatment includes historical perspective and canonical examples, but primarily concentrates on modern statistical methods, computation and implementation in R at modern scale. Rmarkdown facilitates a fully reproducible tour complete with motivation from, application to, and illustration with, compelling real-data examples. Read more →

# STA 265 Notes (Methods of Statistics and Data Science)

## by Christopher Mecklin

This are notes for STA 265 at Murray State University for students in Dr. Christopher Mecklin’s class. […] This chapter includes both material from the textbook and material that I have added to aid you in using R and R Studio for statistical and data science tasks. To both illustrate the 4-Step Process of statistical modeling and to review the two-sample (t)-test, I will illustrate testing to see if there was a statistically significant differnce between two different sections of a class on their final exam, where one section took a final on Monday morning and the other one on Friday … Read more →

# Scientific Research and Methodology

## by Peter K. Dunn

An introduction to quantitative research in science, engineering and health (including research design, hypothesis testing and confidence intervals in common situations) […] This book introduces quantitative research in the scientific and health disciplines. The whole research process is introduced, from asking a research question to analysis and reporting of the data. The main focus, however, is the analysis of data. To support this textbook, the following are also available: These books are both freely available online. Almost every dataset used in this book is a real data-set. Many are … Read more →

# Data Science

## by Tiffany Timbers, Trevor Campbell, and Melissa Lee

This is a textbook for teaching a first introduction to data science. […] Data Science This is the website for Data Science: A First Introduction. You can read the web version of the book on this site. Click a section in the table of contents on the left side of the page to navigate to it. If you are on a mobile device, you may need to open the table of contents first by clicking the menu button on the top left of the page. You can purchase a PDF or print copy of the book on the CRC Press website or on Amazon. This work by Tiffany Timbers, Trevor Campbell, and Melissa Lee is licensed under a … Read more →

# STA 125 Notes (Statistical Reasoning)

## by Christopher Mecklin

This are notes for STA 125 at Murray State University for students in Dr. Christopher Mecklin’s class. […] These notes are meant to supplement, not replace your textbook. I will occasionally cover topics not in your textbook, and I will stress those topics I feel are most important. “Statistical Reasoning” is a new course at Murray State, where the major goal of the course is to become a “consumer” of statistics rather than a “producer” of statistics. Thus, our emphasis will be on the correct interpretation of statistical results that you might run across in the media, particularly as … Read more →

# Introduction to Econometrics with R

## by Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer

Beginners with little background in statistics and econometrics often have a hard time understanding the benefits of having programming skills for learning and applying Econometrics. ‘Introduction to Econometrics with R’ is an interactive companion to the well-received textbook ‘Introduction to Econometrics’ by James H. Stock and Mark W. Watson (2015). It gives a gentle introduction to the essentials of R programming and guides students in implementing the empirical applications presented throughout the textbook using the newly aquired skills. This is supported by interactive programming exercises generated with DataCamp Light and integration of interactive visualizations of central concepts which are based on the flexible JavaScript library D3.js. Read more →

# Introductory Statistics for Economics

## by Brian Krauth

A textbook for an introductory (first-year or second-year undergraduate) course in statistics for economics majors. […] As its name suggests, Introductory Statistics for Economics is a textbook intended for use in an introductory (first or second year) statistics course for economics majors. It was written for use as a textbook for ECON 233, the introductory statistics course for economics majors at Simon Fraser University. The content is similar to most other introductory statistics courses for business and economics students, but with a few important differences. When I was assigned to … Read more →

# Introductory predictive analytics and machine learning in education and healthcare

## by Anshul Kumar

This textbook accompanies the course HE-930 in the PhD in HPEd program at MGH Institute of Health Professions. This book introduces students to basic predictive analytics and machine learning, with examples and applications related to education and healthcare. […] This textbook accompanies the course HE-930—Statistics/Predictive Analytics for Health Professions Education—in the PhD in HPEd program at MGH Institute of Health Professions. HE-930 is a data analytics course that introduces students to basic predictive analytics (PA) and machine learning (ML), with examples and applications … Read more →

# Econometrics for Business Analytics

## by Jose Fernandez

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. [...] These notes have been compiled from the notes I use in my Introduction to Econometrics, Econometrics II, and Data Anaytics class. In many cases, these notes mirror the powerpoint slides avaiable on blackboard. At times, I will add additional details in the text and provide more examples. This text should not be seen as a replacement for the required textbook. The required textbook provides many more examples and ... Read more →

# Statistical Inference via Data Science

## by Chester Ismay and Albert Y. Kim

An open-source and fully-reproducible electronic textbook for teaching statistical inference using tidyverse data science tools. […] This is the website for Statistical Inference via Data Science: A ModernDive into R and the Tidyverse! Visit the GitHub repository for this site and find the book on Amazon. You can also purchase it at CRC Press. This work by Chester Ismay and Albert Y. Kim is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International … Read more →

# R/RStudio Companion

## by Statistics/Data Science

Companion document to Introduction to Statistical Investigations using R/RStudio. […] This companion was designed for use in STAT160 (Introduction to Data Science), however could be used for any intro-level data science course. The textbook for the course is Introduction to Statistical Investigations (Tintle et. al). Through in-class and home work assignments, students will learn to use R and RStudio. In this companion, we will review the commands and functions students will need to perform statistical analysis and generate statistical … Read more →

# _main.knit

## by mathsresources

This textbook is designed to support the Advanced Higher Statistics course. … Read more →

# DSCI 335: Inferential Reasoning in Data Analysis

## by Ben Prytherch

DSCI 335: Inferential Reasoning in Data Analysis […] This book is meant to accompany DSCI 335. It is not a complete textbook; you will need to take notes on what you hear in class and what you read throughout the semester. In it, you will find: This book will likely be updated and revised as the semester progresses. Feel free to read ahead, just don’t be surprised if something … Read more →

# Responsible applied statistics in R for behavioral and health data (working title)

## by Anshul Kumar

This textbook accompanies the course HE-902 in the PhD in HPEd program at MGHIHP (http://mghihp.edu/phdhped). HE-902 is a statistics course that equips students to analyze healthcare and/or behavioral data in R. […] Welcome to HE-902! Please watch the following welcome video: The video above can also be viewed externally at https://youtu.be/DmWQ51aX-ao. Please additionally read the following items: This textbook accompanies the course HE-902—Advanced Statistical Modeling for Health Professions Education—in the PhD in HPEd program at MGH Institute of Health Professions. HE-902 is a … Read more →

# STA 135 Notes (Murray State)

## by Christopher Mecklin

This are notes for STA 135 at Murray State University for students in Dr. Christopher Mecklin’s class. […] These notes are meant to supplement, not replace your textbook. I will occasionally cover topics not in your textbook, and I will stress those topics I feel are most important. My definition of statistics: Statistics is the attempt to use qualitative and quantitative data in order to: When we collect data, we will often organize the data into a table where the rows represent cases or units, which are called subjects or respondents when they are humans, and the columns represent … Read more →

# Macroeconomics

## by Rob Hayward

These are our macroeconomic notes […] These are our lecture notes for the (Carlin and Soskice 2015) textbook. The notes are no substitute for the text which is available in the University of Brighton library. The notes summarise the chapters and add some exercises and links to activities that should assist your understanding of these key macroeconomic topics. There are three broad sections: The New Keynesian Model that brings together aggregate demand, supply and the central bank policy response. The financial system and the global financial crisis that discusses frictions and the … Read more →

# Analysing Data using Linear Models

## by Stéphanie M. van den Berg

This is the data analysis textbook used for study programmes at the faculty of BMS at the University of Twente. […] This book is for bachelor students in social, behavioural and management sciences that want to learn how to analyse their data, with the specific aim to answer research questions. The book has a practical take on data analysis: how to do it, how to interpret the results, and how to report the results. All techniques are presented within the framework of linear models: this includes simple and multiple regression models, linear mixed models and generalised linear models. This … Read more →

# Advanced Statistics I 2021 Edition

The official textbook of PSY 207 for the Fall 2021 Semester. […] This book is a compilation of the readings developed for the Fall 2021 Semester offering of Psychology 207: Advanced Statistics. Please don’t try to sell this book because there are about a million copyright violations in it. … Read more →

# Statistical rethinking with brms, ggplot2, and the tidyverse: Second edition

## by A Solomon Kurz

This book is an attempt to re-express the code in the second edition of McElreath’s textbook, ‘Statistical rethinking.’ His models are re-fit in brms, plots are redone with ggplot2, and the general data wrangling code predominantly follows the tidyverse style. […] This ebook is based on the second edition of Richard McElreath’s (2020a) text, Statistical rethinking: A Bayesian course with examples in R and Stan. My contributions show how to fit the models he covered with Paul Bürkner’s brms package (Bürkner, 2017, 2018, 2022j), which makes it easy to fit Bayesian regression models in R (R … Read more →

# Doing Bayesian Data Analysis in brms and the tidyverse

## by A Solomon Kurz

This project is an attempt to re-express the code in Kruschke’s (2015) textbook. His models are re-fit in brms, plots are redone with ggplot2, and the general data wrangling code predominantly follows the tidyverse style. […] Kruschke began his text with “This book explains how to actually do Bayesian data analysis, by real people (like you), for realistic data (like yours).” In the same way, this project is designed to help those real people do Bayesian data analysis. My contribution is converting Kruschke’s JAGS and Stan code for use in Bürkner’s brms package (Bürkner, 2017, 2018, 2022g), … Read more →

# Statistical rethinking with brms, ggplot2, and the tidyverse

## by A Solomon Kurz

This project is an attempt to re-express the code in McElreath’s textbook. His models are re-fit in brms, plots are redone with ggplot2, and the general data wrangling code predominantly follows the tidyverse style. […] I love McElreath’s (2015) Statistical rethinking text. It’s the entry-level textbook for applied researchers I spent years looking for. McElreath’s freely-available lectures on the book are really great, too. However, I prefer using Bürkner’s brms package (Bürkner, 2017, 2018, 2022i) when doing Bayesian regression in R. It’s just spectacular. I also prefer plotting with … Read more →

# ECON 381: Statistics and Probability for Econometrics

## by Pierangelo DePace and Augusto Gonzalez Bonorino

Textbook for ECON 381: Statistics and Probability for Econometrics […] Here the introduction to the class and … Read more →

# Applied Biostats – BIOL3272 UMN – Fall 2022

## by Yaniv Brandvain

This is the textbook for applied biostats in fall of 2022 taught by yaniv brandvain […] In the summer of 2020, the world was on fire – COVID was raging, we – especially in Minnesota – were processing the murder of George Floyd and the subsequent uprising etc, the future was unclear. At that point teaching was likely to be entirely online, and I decided to write a digital book for my course see the first edition of my book here. I didn’t really know what I was doing or what my vision was (and to some extent I still do not). There were hiccups: some strangeness in rendering etc, typos, last … Read more →

# An Introduction to Statistical Learning with the tidyverse and tidymodels

## by Taylor Dunn

Working through ISLR with the tidyverse and tidymodels […] I am a data scientist and statistician who is (mostly) self-taught from textbooks and generous people sharing their work online. Inspired by projects like Solomon Kurz’s recoding of Statistical Rethinking and Emil Hvitfeldt’s ISLR tidymodels labs, I decided to publicly document my notes and code as I work through An Introduction to Statistical Learning, 2nd edition by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. I prefer to work with the tidyverse collection of R packages, and so will be using those to wrangle … 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 →

# Principles of Statistical Analysis: R Companion

## by Ery Arias-Castro

R code that showcases some of the concepts and tools introduced in Principles of Statistical Analysis […] This is a companion to the textbook Principles of Statistical Analysis. It contains some R code that illustrates the concepts and tools introduced in the textbook. Some familiarity with R is assumed, although no advanced knowledge is required. The code is meant to be relatively simple, yet useful, at least for novices. No real effort was made to optimize it. The chapters are numbered as they are in the textbook, while the sections are not. The data not taken from packages is available … Read more →

# Introduction to Bayesian Econometrics

## by Andrés Ramírez-Hassan

The subject of this textbook is Bayesian regression analysis, and its main aim is to provide introductory level theory foundation, and facilitate applicability of Bayesian inference. […] Since late 90’s Bayesian inference has gained a lot of popularity among researchers due to the computational revolution and availability of algorithms to solve complex integrals. However, many researchers, students and practitioners still lack understanding and application of this inferential approach. The main reason is the requirement of good programming skills. Introduction to Bayesian econometrics: A … Read more →

# Interactive Intermediate Microeconomics

## by Yogi Gohel

This is a minimal example of using the bookdown package to write a book. set in the _output.yml file. The HTML output format for this example is bookdown::bs4_book, [...] This book is designed to help students develop an intuition for intermediate microeconomic concepts using interactive plots and animations. By no means is this a replacement for your course textbook; it should serve as a supplement that builds confidence towards more complex topics. This book is still a work in progress, so there is a chance you will find typos or inconsistencies. Please let me know if you find any at ... Read more →

# An Introduction to Probability and Simulation

## by Kevin Ross

This textbook presents a simulation-based approach to probability, using the Symbulate package. […] Why study probability? Why use simulation to study probability? The examples in this book are used to both motivate new topics and to help you practice your understanding of the material. You should attempt the examples on your own before reading the solutions. To encourage you to do so, the solutions have been hidden. You can reveal the solution by clicking on the Show/hide solution button. Here is where a solution would be, but be sure to think about the problem on your own first! (Careful: … 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 →

# An Introduction to Bayesian Reasoning and Methods

## by Kevin Ross

This textbook presents an introduction to Bayesian reasoning and methods […] Statistics is the science of learning from data. Statistics involves We will assume some familiarity with many of these aspects, and we will focus on the items in italics. That is, we will focus on statistical inference, the process of using data analysis to draw conclusions about a population or process beyond the existing data. “Traditional” hypothesis tests and confidence intervals that you are familiar with are components of “frequestist” statistics. This book will introduce aspects of “Bayesian” statistics. We … Read more →

# Machine Learning for Imbalanced Datasets

## by Nana Boateng

This is a machine learning textbook for dealing with imbalanced datasets […] This is a sample book written in Markdown. You can use anything that Pandoc’s Markdown supports, e.g., a math equation (a^2 + b^2 = c^2). The bookdown package can be installed from CRAN or Github: {r eval=FALSE}install.packages(“bookdown”) # or the development version # devtools::install_github(“rstudio/bookdown”) Remember each Rmd file contains one and only one chapter, and a chapter is defined by the first-level heading #. To compile this example to PDF, you need XeLaTeX. You are recommended to install TinyTeX … Read more →

# R: বাংলায় পরচিতি

## by Mohammad Shamim Hasan Mandal

Written in Bengali, this book is an introductory textbook. […] description: “This is a minimal bookdown demo. It shows the basics of …” github-repo: “rstudio/bookdown-demo” cover-image: “images/cover.png” ** WORK IN PROGRESS ** এই বইটি শেরেবাংলা কৃষি বিশ্ববিদ্যালয়ের কম্পিউটার ক্লাব আয়োজিত R(আর) পরিচিত ক্লাসের জন্য। বইটি আর মার্কডাউন (rmarkdown) দিয়ে লেখা। বইটির লেখায় কোথায় ভুল পেলে অথবা বইটি সম্পর্কে আপনার মতামত জানাতে Email এই বইটি R(আর) সম্পর্কে প্রাথমিক ধারণা দেওয়ার জন্য তৈরি করা হয়েছে। কম্পিউটার প্রোগ্রামিং একটি বড় বিষয়, R(আর) একটি কম্পিউটার প্রোগ্রাম সুতরাং শুধুমাত্র প্রোগ্রামিং নিয়েই অনেক পড়ার সুযোগ রয়েছে। এই বইটির … Read more →

# Physical Geology

## by Karla Panchuk, Steven Earle, and contributors (GitHub/bookdown version maintained by Dewey Dunnington)

“Physical Geology”, adaptaed from Physical Geology: First University of Saskatchewan Edition […] Physical Geology is a comprehensive introductory text on the physical aspects of geology, including rocks and minerals, plate tectonics, earthquakes, volcanoes, mass wasting, climate change, planetary geology and much more. It has a strong emphasis on examples from western Canada. It is adapted from “Physical Geology” written by Steven Earle for the BCcampus Open Textbook Program, and “Physical Geology, First University of Saskatchewan Edition” by Karla Panchuk. The GitHub/bookdown version of … Read more →

# Understanding the Whole Child: Prenatal Development through Adolescence

## by Jennifer Paris, Antoinette Ricardo, & Dawn Rymond

This developmental psychology textbook is about physical, cognitive, and social development during childhood and adolescence. Bookdown adaptation by C. Nathalie Yuen. […] An Open Educational Resources Publication by College of the Canyons Authored and compiled by Jennifer Paris, Antoinette Ricardo, & Dawn Rymond Editor: Alexa Johnson Cover Image: Photo by Rene Bernal on Unsplash Bookdown adaptation: C. Nathalie Yuen This is a derivative of Version 1.2 This textbook is licensed under a Creative Commons Attribution 4.0 License. July 22, 2021 2019 - Version … Read more →

# PSY317L & PSY120R Guidebook

## by James P. Curley & Tyler M. Milewski

PSY317L & PSY120R Guidebook […] This book is written to help students enrolled in the University of Texas at Austin Introduction to Statistics for the Behavioral Sciences (PSY317L) course or R Programming for Behavioral Sciences (PSY120R) led by Professor James Curley. We hope that the book will be a useful resource to help you learn both R and statistics. If you have any suggestions for improvements, please get in touch with Professor Curley. This is in between a textbook and a study guide. We’re trying to build materials that will enable students to quickly find what they’re looking for … 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 →

# Techincal Analysis with R (second edition)

## by Ko Chiu Yu

This is an introductory textbook that focuses on how to use R to do technical analysis. […] Since the first edition has been published in 2018, I have received numerous comments on how to improve the book. The second edition attempts to accommodate these suggestions as much as possible. The book is completely rewritten and reorganized. In particular, the core part of trading rule is now divided into three chapters: day-trading rule, non-day trading rule, and complex trading rule. Day-trading rule requires only basic knowledge of conditional if statements and for loops. Non-day trading … Read more →

# Machine Learning Techniques

## by J.H. van der Zwan

Introductory text to a couple of commonly used Machine Learning techniques and how they are performed in R […] This book is intended to be a reference for frequently used Machine Learning techniques and how they can be performed in R. Writing this work started in summer 2020 and new chapters are and will be added over time. It is written with a view to students pursuing a Machine Learning course in a pre-graduate or graduate program. It is not intended to be an exhaustive textbook on all possible Machine Learning … Read more →

# STAT 205B: Classical Inference

## by Jizhou Kang

This is my E-version notes of the classical inference class in UCSC by Prof. Bruno Sanso, Winter 2020. This notes will mainly contain lecture notes, relevant extra materials (proofs, examples, etc.), as well as solution to selected problems, in my style. The notes will be ordered by time. The goal is to summarize all relevant materials and make them easily accessible in future. The textbook that we used is Casella (&) Berger’s famous book: Classical Inference, Second Edition. Most of the materials in this notes is from the textbook, although extending matrials will be added with reference. … Read more →

# Beyond Multiple Linear Regression

## by Paul Roback and Julie Legler

An applied textbook on generalized linear models and multilevel models for advanced undergraduates, featuring many real, unique data sets. It is intended to be accessible to undergraduate students who have successfully completed a regression course. Even though there is no mathematical prerequisite, we still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. We believe strongly in case studies featuring real data and real research questions; thus, most of the data in the textbook arises from collaborative research conducted by the authors and their students, or from student projects. Our goal is that, after working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling. Read more →

# Introduction to Research Methods

## by Eric van Holm, PhD

This is a textbook written for an Introduction to Research Methods class in the social sciences […] “The true path to wisdom can be identified … it has to have practical application in your life. Otherwise, wisdom becomes a useless thing and deteriorates, like a sword that is never used.” - Paulo Coelho, “The Pilgrimage” This book is intended as a practical introduction to research methods in the social sciences. If you pursue research academically or professionally, it will probably not be the last book you need to read on the subject. This is intended as something of a gentle introduction … Read more →

# Pursuing Truth: A Guide to Critical Thinking

## by Randy Ridenour

This is a textbook for use in undergraduate critical thinking courses. […] This is a textbook written primarily for my students in PHIL 1502: Critical Thinking, at Oklahoma Baptist University in Shawnee, Oklahoma. There are many good textbooks for critical thinking on the market today, so why write another one? First, all of those books were written for someone else’s course. None cover all of the topics that I would like to cover in class. Second, as I’m sure any student can attest to, textbooks are remarkably expensive, to the point that most of the world’s population cannot afford access … Read more →

# Working with Data in R

## by Eric van Holm, PhD

This is a textbook written to introduce some basic steps of working with and preparing data for use in quantitative analysis. […] This book will provide readers a few basic steps to begin working with data in R. It is not meant as a comprehensive introduction to using R for all of the different functions that are possible. Rather, it is tailored to help an individual that has quantitative data they would like to work with, but has not worked in R previously. The presentation of material is meant to be accessible to students with little to no background in R or computer programming. In many … Read more →

# PSY317L Guidebook

## by James P. Curley & Tyler M. Milewski

PSY317L Guidebook […] This books is still in progress !!! This is a draft. Several sections are still incomplete or unedited. This book is written to help students enrolled in the University of Texas at Austin Introduction to Statistics for the Behavioral Sciences (PSY317L) course led by Professor James Curley. We hope that the book will be a useful resource to help you learn both R and statistics. If you have any suggestions for improvements, please get in touch with Professor Curley. This is in between a textbook and a study guide. We’re trying to build materials that will enable students … Read more →

# An Introduction to Web Analytics

## by Michael Hewlett

The best basics of web analytics. […] If I asked you how you wanted to level-up in web analytics, it would be fair if you said “I can’t answer that - I don’t know enough about web analytics to know what I don’t know”. This textbook will take you from “I don’t know what I don’t know” to knowing the content areas of web analytics and broadly knowing what can be done with web analytics skills. In addition to shifting your knowledge base from unknown unknowns to known unknowns, by the end of this textbook, you will be able to take any question that can be addressed with web analytics and answer … Read more →

# Quantitative Research Methods for Political Science, Public Policy and Public Administration for Undergraduates: 1st Edition With Applications in R

## by Wesley Wehde, Hank Jenkins-Smith, Joseph Ripberger, Gary Copeland, Matthew Nowlin, Tyler Hughes, Aaron Fister, and Josie Davis

Quantitative Research Methods for Political Science, Public Policy and Public Administration for Undergraduates: 1st Edition With Applications in R […] The idea for the graduate level version of this book grew over decades of teaching introductory and intermediate quantitative methods classes for graduate students in Political Science and Public Policy at the University of Oklahoma, Texas A&M, and the University of New Mexico. Despite adopting (and then discarding) a wide range of textbooks, we were frustrated with inconsistent terminology, misaligned emphases, mismatched examples and data, … Read more →

# Technical Foundations of Informatics

## by Michael Freeman and Joel Ross

The course reader for INFO 201: Technical Foundations of Informatics. […] Announcement: Starting in 2019, readings for the INFO 201 course will come from the textbook Programming Skills for Data Science, which is available to UW students for free via SafariBooksOnline or in print. Unless specifically directed to a section of this online text, you should refer to the Programming Skills for Data Science textbook. This book covers the foundation skills necessary to start writing computer programs to work with data using modern and reproducible techniques. It requires no technical background. … Read more →

# Quantitative Research Methods for Political Science, Public Policy and Public Administration: 4th Edition With Applications in R

## by Hank Jenkins-Smith, Joseph Ripberger, Gary Copeland, Matthew Nowlin, Tyler Hughes, Aaron Fister, Wesley Wehde, and Josie Davis

Quantitative Research Methods for Political Science, Public Policy and Public Administration: 4th Edition With Applications in R […] The idea for this book grew over decades of teaching introductory and intermediate quantitative methods classes for graduate students in Political Science and Public Policy at the University of Oklahoma, Texas A&M, and the University of New Mexico. Despite adopting (and then discarding) a wide range of textbooks, we were frustrated with inconsistent terminology, misaligned emphases, mismatched examples and data, and (especially) poor connections between the … Read more →

# Statistical Rethinking with brms, ggplot2, and the tidyverse

## by A Solomon Kurz

This project is an attempt to re-express the code in McElreath’s textbook. His models are re-fit in brms, plots are redone with ggplot2, and the general data wrangling code predominantly follows the tidyverse style. […] I love McElreath’s Statistical Rethinking text. It’s the entry-level textbook for applied researchers I spent years looking for. McElreath’s freely-available lectures on the book are really great, too. However, I prefer using Bürkner’s brms package when doing Bayeian regression in R. It’s just spectacular. I also prefer plotting with Wickham’s ggplot2, and coding with … Read more →

# Techincal Analysis with R

## by Ko Chiu Yu

This is an introductory textbook that focuses on how to use R to do technical analysis. […] R is widely used in statistical computation. It is well-suited to do computationally heavy financial analysis. In particular, evaluating performance of trading rule based on technical indicators. Moreover, R can be one-stop solution to the whole procedure of data analysis. A standard procedure of financial data analysis is: You can do all of them inside R without using other software. This short book is a short introduction on how to use R and RStudio to do financial data analysis from the beginning. … Read more →

# BIOL3360 - Analysis and Communication of Biological Data:

## by janengelstaedter

This online textbook contains learning material for the UQ (The University of Queensland) course BIOL3360: Analysis and Communication of Biological Data. This book is organised with each chapter corresponding to lectures from the Mathematical Modelling component of the course. This book contains many code chunks that can be copied and pasted into an R console to create Shiny apps of the models being discussed. Content and figures were created by Jan Engelstädter. Online version including Shiny apps were created by Nicole Fortuna. 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 →

# Probability and Statistics

## by Rob Carroll

These are the lecture notes for POS 5737, the introductory probability and statistics class in the graduate program in political science at Florida State University. […] These are the notes for POS 5737, taught in the Department of Political Science at Florida State University. They freely borrow from several well-known textbooks, including those by Wackerly, Mendenhall, and Scheaffer (2008), DeGroot and Schervish (2012), and Casella and Berger (2002). They also borrow from my own notes as a graduate student when I was taught by Kevin Clarke. Kevin was kind enough to provide his own old … Read more →

# ModernDive

## by Chester Ismay and Albert Y. Kim STARRING FRANK MCGRADE

An open-source and fully-reproducible electronic textbook bridging the gap between traditional introductory statistics and data science courses. […] Help! I’m new to R and RStudio and I need to learn about them! However, I’m completely new to coding! What do I do? If you’re asking yourself this question, then you’ve come to the right place! Start with our Introduction for Students. This is version 0.2.0 of ModernDive published on August 02, 2017. For previous versions of ModernDive, see Section 1.4. This book assumes no prerequisites: no algebra, no calculus, and no prior programming/coding … Read more →

# Forecasting: Principles and Practice (2nd ed)

## by otexts.com

This is the second edition of Forecasting: Principles & Practice, which uses the forecast package in R. The third edition, which uses the fable package, is also available. Welcome to our online textbook on forecasting. This textbook is intended to provide a comprehensive introduction to forecasting methods and to present enough information about each method for readers to be able to use them sensibly. We don’t attempt to give a thorough discussion of the theoretical details behind each method, although the references at the end of each chapter will fill in many of those details. The book is … Read more →

# From Attention to Distraction

## by Alex O. Holcombe

A short textbook on the psychology of attention, mostly visual attention, written for PSYC2016 at the University of Sydney. It uses a principles-based approach with an emphasis on demonstration of the phenomena covered using visual demonstrations: images and animations. […] This is a mini-textbook on attention. It was written for PSYC2016 at the University of Sydney, but is likely to be suitable for everyone. Please let me know about any typos or unclear bits! You can contact me (he/him) via email (alex.holcombe@sydney.edu.au), Mastodon, or twitter. You can read this mini-text here on the … Read more →

# Odds & Ends

## by Jonathan Weisberg

An open access textbook for introductory philosophy courses on probability and inductive logic. […] This textbook is for introductory philosophy courses on probability and inductive logic. It is based on a typical such course I teach at the University of Toronto, where we offer “Probability & Inductive Logic” in the second year, alongside the usual deductive logic intro.(,) The book assumes no deductive logic. The early chapters introduce the little that’s used. In fact almost no formal background is presumed, only very simple high school algebra. Several well known predecessors inspired … Read more →