Topic: Ethics, Data Quality and Reproducible Work

Structuring Data in Rows and Columns

Standardizing Inconsistent Category Labels

Secure Handling of Sensitive Data

Reproducible Analysis With Scripts

Reproducible Data-Cleaning Project

Reporting Results Without Misleading Readers

Recording Data Provenance

Recognizing and Recording Missing Values

Quality Checks Before Analyzing Data

Privacy, Confidentiality, and Anonymity