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Data Science Event

Data collected in time and/or space exhibit unique properties that require attention to draw proper conclusions from statistical analyses. In this workshop, students are introduced to statistical concepts that are particularly useful for analyzing spatial-temporal data.

Using R and Python, students will learn the basic mathematics of spatial-temporal analysis via hands-on exercises, and will put the concepts to practice analyzing real datasets from the environmental sciences. Key R packages will be used in the workshop, while Python functionality to call R from within Python will also be provided, therefore accommodating both R and Python users. An introductory knowledge of either R or Python is therefore required to take part in the exercises. A background with either one statistics course or some experience analyzing spatial and/or temporal data is also recommended. While the datasets are drawn from the environmental sciences, the concepts apply equally across disciplines where data are collected in time and/or space.

Date: April 27, 2017

Time:9 a.m. to 5 p.m. with lunch provided

Location: Donald Bren Hall, Room 4011

Instructor:  Gregory Britten, Yara Mohajerani, UC Irvine

Pre-requisites: 1) familiarity with basic statistical concepts, and 2) intermediate R or Python programming knowledge. For the tutorial, bring a laptop with R or Python downloaded and installed and WiFi.