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Avis et commentaires pour d'étudiants pour Statistical Inference and Hypothesis Testing in Data Science Applications par Université du Colorado à Boulder

11 évaluations

À propos du cours

This course will focus on theory and implementation of hypothesis testing, especially as it relates to applications in data science. Students will learn to use hypothesis tests to make informed decisions from data. Special attention will be given to the general logic of hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. Attention will also be given to the misuse of testing concepts, especially p-values, and the ethical implications of such misuse. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at

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1 - 3 sur 3 Avis pour Statistical Inference and Hypothesis Testing in Data Science Applications

par Nathan H

10 janv. 2022

I​t's clear that a good bit of thought and effort went into putting the course together, but it seems unfinished.

The autograder system on the programming assignments in the three University of Colorado Boulder statistics courses that I've enrolled in is like something from a Kafka novel. It does not provide feedback on which questions it's marking incorrect, and Jupyter notebooks are unreliable in their rention of updates. That can compound with errors in the assignments themselves and a nearly deserted discussion forum for a really rough time.

T​here's not enough student course work to make me confident in my mastery of the material or in the retention of it.

I​t would be nice to have some reference material other than the lecture slides.

I​t's not particular to this course, but there are a lot of irritations with the Coursera UI. (For example, I would like to access the course while writing this review to confirm that my comments are accurate, but that's not easy to do.)

par Garima V

27 juil. 2022

Loved the material. Content looks quite convincing and well explained!

par Ricardo R

11 juil. 2022

excelentes aplicabilidades