Roboforbes

STAT GR5293

Topics in Modern Statistics · Statistics

Topics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly…

Who teaches STAT GR5293

What students said

Jeremy Shen · 2026 · 2026

image analysis, image enhancement, iris recognition, convolution, clustering, brain encoding decoding

Mark Hansen · 2022 · 2022

Knowledge about communicating data and statistics. I learnt how to convey data and statistics effectively to different audiences. In addition, I expanded my horizon in communication and journalism from the talking of various guest speakers.

Andrew Gelman · 2025 · 2025

I learned how to fit and build hierarchical multilevel regression models in R.

Joyce Robbins · 2025 · 2025

interpretable machine learning packages/methods/graphing types/algorithms

Wayne Lee · Spring 2022 · 2022

Mark and Wayne seemed to have pretty different ideas for this class, both brilliant, but it was obvious that they often disagreed which made the class a bit difficult and awkward at times. 1 Columbia University: Arts & Sciences Spring 2022 Course: STATGR5293+JOUR6002 : Computational Journalism Instructor: Wayne Lee

Jeonghoe Lee · 2025 · 2025

Several financial concepts including BASEL and some common technical indicators.

Katharina Schultebraucks · 2022 · 2022

This course is an excellent blend of theory and praxis. I enjoyed learning about the challenges and strengths of healthcare algorithms. The professor is very knowledgeable!

Marco Avella Medina · 2023 · 2023

Robust statistics. M-estimators. Robust linear regression etc.

Jeremy Shen · 2026 · 2026

I learned how to load, view, manipulate, and save imaged using CV2 in Python; preprocess and enhance images; analyze histograms, projections, contours, and other elements of an image to accomplish tasks like segmentation; implement object recognition; apply certain machine learning techniques to classify/match images and/or their features; use SPM fMRI analysis in MATLAB; relate human vision to computer vision, particularly in how images are understood by the computer as matrices with pixel value intensities; understand some theory behind signals, frequency, noise, etc.

Mark Hansen · 2022 · 2022

how to communicate data/numbers in a variety of settings.

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