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學生對 密歇根大学 提供的 Fitting Statistical Models to Data with Python 的評價和反饋

4.4
583 個評分
107 條評論

課程概述

In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course (Course 2) to emphasize the importance of connecting research questions to our data analysis methods. We will also focus on various modeling objectives, including making inference about relationships between variables and generating predictions for future observations. This course will introduce and explore various statistical modeling techniques, including linear regression, logistic regression, generalized linear models, hierarchical and mixed effects (or multilevel) models, and Bayesian inference techniques. All techniques will be illustrated using a variety of real data sets, and the course will emphasize different modeling approaches for different types of data sets, depending on the study design underlying the data (referring back to Course 1, Understanding and Visualizing Data with Python). During these lab-based sessions, learners will work through tutorials focusing on specific case studies to help solidify the week’s statistical concepts, which will include further deep dives into Python libraries including Statsmodels, Pandas, and Seaborn. This course utilizes the Jupyter Notebook environment within Coursera....

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BS
2020年1月17日

I am very thankful to you sir.. i have learned so much great things through this course.\n\nthis course is very helpful for my career. i would like to learn more courses from you. thank you so much.

AF
2019年3月11日

The course is actually pretty good, however the mix between basic subjects (like univariate linear regression) and relatively advanced topics (marginal models) may discourage some students.

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26 - Fitting Statistical Models to Data with Python 的 50 個評論(共 110 個)

創建者 Walt T S L

2020年11月20日

Great statistical lessons, I did not realize there were more regression-type models besides Ordinary Least Squares, which expanded my learning horizon, and of course, applied using Python Jupyter Notebooks. Python Code was comprehensive and enabled easy following. It was immensely helpful as I did not know how to even begin constructing a linear model study, using independent or dependent data.

創建者 ellie c

2020年8月15日

The most difficult course in this specification! The most important takeaway point of this course is to understand why we choose any model to fit our data, and how to interpret the model. Don't jump into complex math calculation, we got python to do that for us! Dr Brady did a very good job conveying those ideas to us.

p.s the forum has great discussion posts, make sure to use the forum.

創建者 William S

2021年10月5日

I have learnt to applying coding in statistical analysis. I really enjoyed the Week 4 Bayesian Statistics because the use of coding has added new favor to this topic. It makes the study a real science but not something set in the stone (textbook).

創建者 ARVIND K S

2020年4月7日

A great course on how to fit models to data. Very rich on theoretical concepts and equally great on the practical aspects of using python to fine-tune your model, viewing the same each time as you modify data. Very fine course indeed

創建者 Bharti S

2020年1月18日

I am very thankful to you sir.. i have learned so much great things through this course.

this course is very helpful for my career. i would like to learn more courses from you. thank you so much.

創建者 Alvaro F

2019年3月12日

The course is actually pretty good, however the mix between basic subjects (like univariate linear regression) and relatively advanced topics (marginal models) may discourage some students.

創建者 Kylie A

2021年7月12日

Just like the other courses in the specialization, very well thought out and planned! Up to date, great professors . . . couldn't ask for more!

創建者 Varga I K

2019年4月14日

Great review of machine learning used in statistics finished up with some overview on bayesian math.

Enjoyed very much and learnt even more.

創建者 Camila B V

2021年6月28日

Excellent, the explanations were perfect and its theorical focus was the thing why I loved this course.

創建者 Yamala K R

2021年1月12日

These whole three certifications lays the foundation for learning Machine Learning a more in-depth way.

創建者 Xinyuan G

2020年6月15日

The specialization covers important practical topics. I am glad to have the opportunity to explore it.

創建者 Alexander B

2020年5月28日

Overall really great coure that covers a lot of material in a concise way.

創建者 Tarit G

2020年7月4日

Excellent course! Thanks to the instructors and the team made this MOOC.

創建者 Rodrigo E P M

2020年8月23日

An excellent introductory course to the world of statistical modeling.

創建者 Nicky D

2020年1月22日

Excellent course, really enjoyed the section on Bayesian statistics.

創建者 nipunjeet s g

2019年5月25日

Very informative and the example

applications are extremely detailed

創建者 Prabakaran C

2020年3月17日

Have given me CLearcut idea about Mixed-effects and Marginal Models

創建者 Hrishi P

2020年6月11日

Great practical applications of statistics with Python!

創建者 DIBYA P S

2020年6月21日

good conceptual development , helped lot in learning

創建者 Harish S

2019年1月27日

Content of course was good. Some issue with quiz.

創建者 Appi

2019年9月23日

Very good instructors and very good workload!

創建者 Debabrata A K S

2020年2月19日

Very nice course. Well explained kudos.

創建者 Sumit M

2020年3月30日

Very Very Good For learning Statistics

創建者 JamieLiu

2021年9月8日

Great course ,I learned a lot from it

創建者 SHIVAM A

2021年6月2日

awesome course teaching and materials