IDS-RDM-202019-FSFDAWR
Repository for Foundation Skills for Data Analysis with R
IDS-RDM-202019 Foundation Skills for Data Analysis with R
This repository contains a collection of R tutorials, developed at the University of Maastricht for University Library - RDM Support @UM that use R software.
The goal is to organize relevant material into modular components, for more efficient design and maintenance of material, that can be used across courses, and that are accessible to students during and after their studies.
About this course
IDS aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with social science data in R.
This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 8 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to inferential statistics. All lessons demonstrate how to work with databases directly from R.
Learning outcomes
The curriculum for these students will be:
- Introduction to R
- Introduction to Exploratory Data Analysis
- Create graphs for exploring your data
- Research Data Management
- Interpret Pearson correlation and scatter plots
- Loop functions in R
- Inferential Statistics
Level: Beginner
Duration: 5 weeks
Weekly study: 2 hours
Course type: Online
Course details:
Modules: 5
| Modules | Hours | Description |
|---|---|---|
| 1 | 0:20 | Introduction to Stats with R |
| 2 | 0:30 | Descriptive Statistics |
| 3 | 0:40 | Inferential Statistics I |
| 4 | 0:40 | Inferential Statistics II |
| 5 | 0:40 | Inferential Statistics III |
Assignments: 5
| Tutorial | Schedule | Learning Outcomes |
|---|---|---|
| Intro to R | 00:55 | What are the essential compoments of R stats? |
| Exploratory Data Analysis | 02:00 | What are the steps for Exploratory Data Analysis? |
| Inferential Statistics I | 03:30 | How to conduct and interpret t-test in R? |
| Inferential Statistics II | 05:00 | How to conduct and interpret ANOVA & Chi square test? |
| Inferential Statistics II | 06:30 | How to conduct and interpret linear & logistic regression? |
Course Syllabus
License
Code
The code in this repository, including all code samples in the notebooks listed above, is released under the MIT license. Read more at the Open Source Initiative.
Text
The text content of the book is released under the CC-BY-NC-ND license. Read more at Creative Commons.