This is the seminar handbook for systematic reviewing scientific literature that outlines the weekly tasks for each seminar […] This module aims to develop student’s knowledge and understanding of the systematic reviewing of academic literature. This includes developing an appropriate search string, screening process, study eligibility criteria, data extraction form/table, quality appraisal tool and other methodological features associated with the systematic reviewing process. This process minimises potential reviewer biases and increases the methodological rigor. Using these skills … Read more →

This book is an overview of how practitioners can acquire, wrangle, visualize, and model data with the R and Stan. […] 你好，这里是四川师范大学研究生公选课《数据科学中的R语言》的课程内容。R语言是统计编程的第一语言，近几年Tidyverse的推出大大降低了R语言的学习难度。Tidyverse是一系列R包的集合，包含了dplyr、ggplot2、tidyr、stringr等，从数据导入预处理，再到高级转化、可视化、建模和展示。因为其代码清晰可读的编程风格，得到越来越多人的喜爱。考虑到大家来自不同的学院，有着不同的学科背景，因此讲授的内容不会太深奥（要有信 … Read more →

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 →

R Basics […] Reference : R for Beginners. R has 6 data types. R will save data when you assign it to the variable. With n <- 15, n is set to numeric, We can use various operations(methods) with numeric type variables. For example, Note also that we can get access to stored data 15 by the variable name n. In addition, we can coerce the object n to be a integer type variable. By enclosing a string with double quotes, we create a character type object, To define a logical object, we type R can interpret 0 as FALSE, other numbers as TRUE Google NaN NULL NA in R or type ?NA ?NaN ?NULL. Unlike … Read more →

R Programlama - Başlangıç […] R’da atama işlemi için “=” ve ya “<-” operatörleri kullanılır. Bir nesneye atama yapılırken sıkça kullanılan “<-” operatörüdür. Fonksiyonların içinde ise “=” operatörü kullanılır. Önceden oluşturulmuş bir nesnenin üzerine tekrar atama işlemi yapılır o nesne en son atanan değeri alır, önceki değer silinir. Nesneyi çağırdığımızda değerini görebiliriz Character ve string atamalarında " " kullanılır. Bir nesnenin class’ını görmek için class() fonksiyonundan yararlanılabilir. Sıkça kullanılan classlardan bir tanesi logical(mantıksal). “Global Environment”’dan silmek … Read more →

This place is for writing regression book. […] Before we talk about regression theory, we need to review some basic statistical inference methods and matrix algebra. This book referred from many books including rowlings’ “Applied Regression Analysis: A research Tool”. (\beta=(\mathbf{X’X})^{-1}\mathbf{X’y}). A matrix is a square shape array of numbers (sometimes can be string). In this book, boldface letters mean matrices. For example, [ \mathbf{A}= \begin{pmatrix} 65 & 154 \ 73 & 182 \ 68 &167 \end{pmatrix}. ] This is a sample book written in Markdown. You can use anything that … Read more →

This book aims to provide a panoramic perspective of the wide array of string manipulations that you can perform with R. If you are new to R, or lack experience working with character data, this book will help you get started with the basics of handling strings. Likewise, if you are already familiar with R, you will find material that shows you how to do more advanced string and text processing operations. Read more →