Semester.ly

Johns Hopkins University | EN.550.439

Time Series Analysis

3.0

credits

Average Course Rating

(3.8)

Time series analysis from the frequency and time domain approaches. Descriptive techniques; regression analysis; trends, smoothing, prediction; linear systems; serial correlation; stationary processes; spectral analysis.

Spring 2013

(3.94)

Spring 2014

(4.13)

Spring 2015

(3.32)

Spring 2013

Professor: Fred Torcaso

(3.94)

The best aspects of this course included the many proofs provided in class, the even blend of theory and application, and the instructor’s wil ingness to help students with the material. Some students felt the pace of the class throughout the semester was too slow. One suggestion was to provide summary slides at the end of each chapter. Another suggestion included incorporating more “hands-on” homework assignments. Prospective students should review the basics of linear algebra and statistical mathematics before taking this course.

Spring 2014

Professor: Fred Torcaso

(4.13)

The best aspects of this course were the lecture style of the instructor, the amount of material covered, and the pace of the course. The instructor worked though problems on the chalkboard, something many students found helpful. The worst aspects of the course were the lack of regression analysis and coding, and the numerous snow days. More practical problems and a more structured section were suggested improvements to the course. Prospective students should know that to do well you wil need a background in proof-based mathematics. The course is challenging but rewarding and interesting.

Spring 2015

Professor: Fred Torcaso

(3.32)

The best aspects of this course were the manageable workload and good introduction to subject matter that was interesting and challenging. Some students found the assignments to be difficult and learning objectives hard to fol ow due to multiple cancel ed classes. Suggestions for improvement included having more organized lectures and pacing the course better. Students also suggested providing more guidance with homework and practice problems. Prospective students should have a background in probability and statistics. Prospective students should also attend lecture and do assigned readings in