EESC6664 · Earth and Environmental Sciences

Environmental Data Exploration and Analysis

Morrissey College of Arts & Sciences

Numerical ratings

4.6 / 5Course rating

From 2 rating records
Across 1 instructor

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Who teaches this? 1

Both ratings are out of 5, for each instructor’s sections of EESC6664.

Hilary Palevsky

Assistant Professor, Earth & Environmental Sciences

2 evaluations for this course

Instructor: 4.8
Course: 4.6

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Hilary Palevsky

Assistant Professor, Earth & Environmental Sciences

2 evaluations for this course

Instructor: 4.8
Course: 4.6

About this course

Earth and environmental science increasingly depends on scientific programming to explore and analyze large datasets from in situ and autonomous observations, satellite remote sensing, and numerical model output. In this course, students will learn to use MATLAB to visualize earth system data across broad spatial and temporal scales in maps and time-series plots and apply statistical tools to analyze trends and variability in their datasets. Students will also learn to critically assess datasets and to select and justify appropriate data sources and analytical methods to address scientific questions about earth system processes. Students will practice these skills in a series of data analysis assignments focused on regional and global climate data and will apply them in a team-based final research project.

All evaluation ratings

Averages use numerical 1–5 ratings, including the ratings submitted with new anonymous reviews.

OrganizationHow well the course was organized: 4.90 / 5
ChallengeHow intellectually challenging students found it: 4.30 / 5
AttendanceHow necessary attendance was: 4.20 / 5
AssignmentsHow helpful assignments were: 4.90 / 5

Weekly effort: ~7 hours

Estimated from the original workload response buckets. Individual sections may differ.

Evaluation history Browse all evaluations

Evaluation history 2 terms

All available terms for EESC6664. Numerical averages use the five-point scale.
Term	Evaluations	Course rating	Instructor rating
Spring 2024	1	5.0	5.0
Spring 2022	1	4.2	4.6