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Basic Statistics in Python (ANOVA)(으)로 돌아가기

Coursera Project Network의 Basic Statistics in Python (ANOVA) 학습자 리뷰 및 피드백

27개의 평가

강좌 소개

In this 1-hour long project-based course, you will learn how to set up a Google Colab notebook, source data from the internet, load data into Python, merge two datasets, clean data, perform exploratory data analysis, carry out ANOVA and create boxplots. Throughout the course you will work on an Education dataset from World Bank. This will allow you to perform statistical analysis on your own datasets in Python. This project does not require any previous Python or coding experience, but it would be useful for learners to understand the statistical methods covered. The course includes data sourcing and cleaning which are invaluable real world skills, and focuses on visualizing your results which is needed as a large part of any analysis is the storytelling....

최상위 리뷰

필터링 기준:

Basic Statistics in Python (ANOVA)의 10개 리뷰 중 1~10

교육 기관: Acacio P

2021년 4월 22일

This a great course, but I'd like to have more explanation about how we could interpret the results from ANOVA.

교육 기관: Olga D

2021년 3월 1일

This project provides step-by-step guidance into accessing the well-structured data files from the web, cleaning them, and later visualizing. This project requires the usage of the basic operations of data processing and essentials in data plotting. However, in order to be able to follow the project, a basic understanding of Python is necessary. So for those who have them, the project might be too easy. Unfortunately, it was not properly explained how to understand the obtained statistical parameters and what they indicate.

교육 기관: Dony E A

2021년 3월 31일

very helpful

교육 기관: Mohamad F H

2021년 2월 21일

Nice Course

교육 기관: Aya A D

2021년 2월 12일


교육 기관: Shaik S

2020년 11월 8일

i loved it.

교육 기관: yoona_gou

2021년 6월 17일


교육 기관: Goh J H

2020년 11월 13일


교육 기관: Julius B

2022년 5월 3일

Google Colab was great

교육 기관: Joe W

2022년 5월 4일

Dataset used for this project is unavailable as of 04 May 2022.

Audio rendering is difficult to understand and comes across as "mumbling" into microphone.

Not possible to retrieve the specific dataset from the World Bank used by the instructor.

Moreover, the dataset is too large to illustrate a simple problem of displaying bunch of boxplots.

I'm very disappointed in having wasted several hours on the project.