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data-cleaning/EESW2019_tutorial: Materials for the short course at the European Establishment Statistics Workshop 2019

Materials for the short course on Statistical Data Cleaning for Business Statistics at the European Establishment Statistics Workshop 2019

Slot 1

Topic time (m) Introduction 20 Reading dirty data 30 Approximate matching 50 Data validation 50

Slot 2

Topic time (m) Error localization 20 Imputation 50 Adjusting 20 Monitoring 30 Wrap-up 10

The course form is highly hands-on. Each topic starts with an approximately 10-15 minute session where you run and adapt some R code. Next, I will provide background and details on what you just did. After that there is a more in-depth assignment. Depending on time and topic we will discuss the topic more in-depth after that.

Bring a laptop

Participants are expected to have a basic knowledge of R/RStudio, explicitly:

Work with the R command line and R scripts
Read/write CSV data
Some basic data manipulations and plots
I highly recommend working with RStudio projects.

Software needed for the course

R See https://r-project.org
(Recommended) Rstudio

Execute the following R code to install the necessary packages.

install.packages(c(
        "validate"
      , "errorlocate"
      , "simputation"
      , "rspa"
      , "daff"
      , "jsonlite"
      , "XML"
      , "readr"
      , "stringr"
      , "lumberjack")
  , dependencies=TRUE)

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