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Unit of study_

Data Wrangling - OLET5606

Year - 2020

Data comes in many and varied formats, it can be tall or wide, big or small, structured or unstructured. Regardless of where you get your data from, it will almost always require some wrangling. Data wrangling is the convolution, alignment and preparation of data before use. This unit provides an overview of best practices in organising your research data from the point of discovery through to its use for scientific applications. You will learn the principles of data handling and how to maintain rigour and integrity of your data throughout your research, including documenting data provenance, how to access major databases, and data licensing. After calculating summary statistics to aid in the identification of outliers and missing values, you will learn how to clean and wrangle data in a reproducible manner in R, at a variety of scales. You will "wrangle" your research data using R, identifying outliers and missing values and ensuring provenance.

3 x 2-3-hr 'live labs'

2 x online quizzes (15% each, total 30%), oral presentation (30%), written report (40%)

Data Wrangling with R (Boehmke, B, 2016)

Assumed knowledge
Basic exploratory data analysis, basic coding in R


Faculty: Science

Intensive July

22 Jun 2020

Department/School: Mathematics and Statistics Academic Operations
Study Mode: Block mode
Census Date: 10 Jul 2020
Unit of study level: Postgraduate
Credit points: 2.0
EFTSL: 0.042
Available for study abroad and exchange: Yes
Faculty/department permission required? No
More details
Unit of Study coordinator: Di Warren
HECS Band: 2
Courses that offer this unit

Non-award/non-degree study If you wish to undertake one or more units of study (subjects) for your own interest but not towards a degree, you may enrol in single units as a non-award student. Cross-institutional study If you are from another Australian tertiary institution you may be permitted to undertake cross-institutional study in one or more units of study at the University of Sydney.

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