In hneth/i2ds: Introduction to Data Science

## Packages: ----- 

library(rmarkdown)
library(knitr)
# library(rmdformats)
# library(tidyverse)
# library(here)

# Own packages: 
library(unikn)
library(ds4psy)

## Housekeeping: -----

# here()
fileName <- "README.Rmd"

## Global options: ----- 

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

# URLs:

# (1) ds4psy: ------ 
url_ds4psy_book <- "https://bookdown.org/hneth/ds4psy/"
url_ds4psy_cran <- "https://CRAN.R-project.org/package=ds4psy"

# ds4psy course in Fall 2020:
# Data Science for Psychologists | PSY-15150 
# 02.11.2020 - 08.02.2021
# weekly on Mon 15:15 - 16:45
# Room R 513/online
url_ds4psy_ilias <- "https://ilias.uni-konstanz.de/ilias/goto_ilias_uni_crs_1077327.html"  # ds4psy
url_ds4psy_zeus  <- "https://zeus.uni-konstanz.de:443/hioserver/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=5101&periodId=181" 

# ds4psy course in Summer 2021:
# Data Science for Psychologists | PSY-15150 
# 12.04.2021 - 19.07.2021
# weekly on Mon 15:15 - 16:45 | online
url_ds4psy_ilias <- "https://ilias.uni-konstanz.de/ilias/goto_ilias_uni_crs_1173220.html"  # ds4psy
url_ds4psy_zeus  <- "https://zeus.uni-konstanz.de:443/hioserver/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=5101&periodId=555"

# i2ds course in Fall 2020: 
# Introduction to Data Science 1: Foundations (using R, ADILT) | PSY-16620 
# 05.11.2020 - 11.02.2021
# weekly on Thu 13:30 - 15:00 | Room C 336/online 
# url_i2ds_ilias <- "https://ilias.uni-konstanz.de/ilias/goto_ilias_uni_crs_1077339.html"
# url_i2ds_zeus  <- "https://zeus.uni-konstanz.de:443/hioserver/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=86706&periodId=181" 

# ds4psy course in Summer 2022:
# Data Science for Psychologists | PSY-15150 
# 11.04.2022 - 18.07.2022 
# weekly on Mon 13:30 - 15:00 | D430 
url_ds4psy_ilias <- "https://ilias.uni-konstanz.de/goto.php?target=crs_1391467"  # ds4psy ilias 
url_ds4psy_zeus  <- "https://zeus.uni-konstanz.de:443/hioserver/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=5101&periodId=557&navigationPosition=hisinoneLehrorganisation,examEventOverviewOwn"  # ds4psy ZEuS


# (2) i2ds: ------ 
url_i2ds_book  <- "https://bookdown.org/hneth/i2ds/"

# i2ds_2 course in Summer 2021: 
# Introduction to Data Science 2: Applications (using R, ADILT) | PSY-16710 
# 15.04.2021 - 22.07.2024 
# weekly on Thu 15:15 - 16:45 | online 
# url_i2ds_ilias <- "https://ilias.uni-konstanz.de/ilias/goto_ilias_uni_crs_1179622.html"
# url_i2ds_zeus  <- "https://zeus.uni-konstanz.de:443/hioserver/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=93121&periodId=555" 

# i2ds_2 course in Summer 2022: 
# Introduction to Data Science 2: Applications (using R, ADILT) | PSY-16710 
# 11.04.2022 - 18.07.2022
# weekly on Mon 15:15 - 16:45 | D430  
url_i2ds_ilias <- "https://ilias.uni-konstanz.de/goto_ILIASKONSTANZ_crs_1392107.html" # i2ds_2 ilias 
url_i2ds_zeus  <- "https://zeus.uni-konstanz.de:443/hioserver/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=93121&periodId=557&navigationPosition=hisinoneLehrorganisation,examEventOverviewOwn" # i2ds_2 ZEuS 

# i2ds_1 course in Fall 2023/2024:  +++ here now +++
# Introduction to Data Science 1: Basics (using R, ADILT) | PSY-16620  
# 23.10.2023 - 05.02.2024 
# weekly on Mon 13:30 - 15:00 (14 sessions) | D435
url_i2ds_ilias <- "https://ilias.uni-konstanz.de/goto.php?target=crs_1633875" # i2ds_1 ilias
url_i2ds_zeus  <- "https://zeus.uni-konstanz.de:443/hioserver/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=86706&periodId=791" # i2ds_1 ZEuS 

# (3) OTHER/OLDER URLs: ------ 

# ossd: ------ 

# SoSe 2023:
# Open Source Software Development in R (ADILT Applications) 
# PSY-18040 
# Tue:  13:30 - 15:00 | C426

url_ossd_ilias <- "https://ilias.uni-konstanz.de/goto_ILIASKONSTANZ_crs_1559797.html"
url_ossd_zeus <- "https://zeus.uni-konstanz.de:443/hioserver/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=102164&periodId=790"

# SoSe 2020:
# url_ds4psy_ilias <- "https://ilias.uni-konstanz.de/ilias/goto_ilias_uni_crs_979923.html"
# url_ds4psy_zeus  <- "https://zeus.uni-konstanz.de:443/hioserver/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=5101&periodId=173"
# # Other:
url_ds4psy_rpository <- "http://rpository.com/ds4psy/"  # Syllabus

# ADILT: 
url_ADILT    <- "https://www.uni-konstanz.de/adilt/"
url_ADILT_en <- "https://www.uni-konstanz.de/en/adilt/"

# Other course-related variables:
ds_project_due  <- lubridate::ymd("2024-02-28")
frm_ds_deadline <- "%A, %B %e, %Y"
# format(ds_project_due, frm_ds_deadline)

Introduction to Data Science (i2ds)

The R package i2ds supports the course Introduction to Data Science (using R, ADILT) at the University of Konstanz.

The i2ds package provides datasets and functions used in the examples and exercises of the book Introduction to Data Science (by Hansjoerg Neth, University of Konstanz, 2023), available at <r url_i2ds_book>. The book and course provide a gentle introduction into the principles and methods of data science to students of psychology and other natural or social sciences. The R package i2ds primarily provides datasets, but also functions for data generation and manipulation that are used in the book's examples and exercises. All functions included in i2ds are designed to be explicit and instructive, rather than efficient or elegant.

The textbook Introduction to Data Science is available at <r url_i2ds_book>.

Description

This course provides a gentle introduction to data science for students of any discipline with little or no background in data analysis or computer programming. Based on notions of representation, measurement, and modeling, we examine key data types (e.g., logicals, numbers, text) and learn to clean, summarize, transform, and visualize (rectangular) data. By reflecting on the relations between representations, tasks, and tools, the course promotes data literacy and cultivates reproducible research practices that precede and enable practical uses of programming or statistics.

The course uses the technologies provided by R [@R-base], RStudio, RMarkdown, including key packages of the tidyverse [@tidyverse] (e.g., dplyr, ggplot2, tibble, and tidyr).

Coordinates

Introduction to data science: Basics (using R, ADILT) (PSY-16620) at the University of Konstanz by Hansjörg Neth (h.neth@uni.kn, SPDS, office D507).
Autumn/Winter 2023: Mondays, 13:30--15:00, D435.
Course materials:
- Ebook Introduction to Data Science (at <r url_i2ds_book>)
- Ebook Data Science for Psychologists (at <r url_ds4psy_book>)
- R package ds4psy (at <r url_ds4psy_cran>)
Online platforms (at uni.kn):
- ZEuS registration system
- Ilias course management system

An initial syllabus for Introduction to Data Science is available at <r url_i2ds_book>.
The organizational details for this course are available on the ZEuS and Ilias web platforms.
The textbook Data Science for Psychologists is available at <r url_ds4psy_book>.
Information on the Advanced Data and Information Literacy Track (ADILT) (en).

Readings

The main sript for this course is yet to be written. A textbook fragment Introduction to Data Science is:

Neth, H. (forthcoming). i2ds: Introduction to Data Science.
Social Psychology and Decision Sciences, University of Konstanz, Germany.
Textbook (version 0.0.1, planned for\ 2023).
Available at <r url_i2ds_book>.

In the meantime, we will be using several chapters from the textbook [-@ds4psyBook]:

Neth, H. (2023). ds4psy: Data Science for Psychologists.
Social Psychology and Decision Sciences, University of Konstanz, Germany.
Textbook and R package (version 1.0.0, September 15, 2023). Available at <r url_ds4psy_book>.

The URL of the supporting R package ds4psy [-@R-ds4psy] is <r url_ds4psy_cran>.

Chapters from the following textbooks [@mdsr; @JamesEtAl2021] are used for individual topics:

Baumer, B. S., Kaplan, D. T., & Horton, N. J. (2021). Modern Data Science with R (2nd ed.).
CRC Press, Taylor & Francis Group, Boca Raton/London/New York.
Available at https://mdsr-book.github.io/mdsr2e/.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An introduction to statistical learning (2nd edition). Springer, New York, NY.
Available at https://www.statlearning.com.

Additional details or readings may be announced if they are needed for individual sessions.