返回到 Fitting Statistical Models to Data with Python

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31 条评论

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....

Jan 18, 2020

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.

Mar 12, 2019

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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创建者 Aayush G

•May 29, 2019

I must say that this is a must take course for ones who are aspiring a career in Data Science. All the concepts were laid out so beautifully and it was explained very clearly with visualisations of each real-life-examples. I enrolled in this specialisation before starting my Machine Learning so that I have all the necessary fundamentals of Statistics. Brady Sir & Brendra Ma'am are simply phenomenal, the way they explain the concepts are incredible. The concepts gets etched in one's memory.

创建者 Tobias R

•Mar 10, 2019

The content itself is great but some notebooks were a bit unready. Otherwise great course!

创建者 David Z

•Feb 10, 2019

Great lecture content, poor quiz design. Hard to apply any of the concepts that you learn.

创建者 Kristoffer H

•Jan 13, 2019

If you don't already understand the topic don't bother with this course, the lectures are 95% hand waving and showing formulas they don't explain how to make sense of and then the quizzes are answering questions on what they didn't bother to explain.

创建者 Flo

•Mar 23, 2020

The most impressive part is Week 2 Linear and Logistic Regression model fitting, Professor Brenda is Brilliant! She has the magic to explain complicated and abstract concept into a very easily understandable ones. Thanks her a lot! Also I was impressive on Week 4 Bayesian approaches courses. Thanks Mark Kurzeja. I think He is a very qualified teacher and prepare for this course content very careful and take it seriously. He also gives a very clear mind to understand those abstract statistic concept!

Overall, the series of Statistic with Python are impressive! You can really learn something useful and the course design is scientific. All teachers in all courses are very good!

创建者 HUNG H L

•Aug 01, 2019

Thank you for creating this course. I have learned basic knowledge to succeed my incoming business education. I have a bachelor degree of laws and am transferring to a master of management. I used this course to learn the prior knowledge that I need about statistics. I finished this specialization and feel more confident about the numerical analysis. Thank you again Michigan Online for your great courses!

创建者 Jafed E

•Jul 06, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

创建者 Bharti S

•Jan 18, 2020

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.

创建者 Alvaro F

•Mar 12, 2019

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.

创建者 Vinícius G d O

•Sep 18, 2019

Good course, but the last of three was the most difficult one. I hope that it were a good introduction to the fascinating world of statistics and data science

创建者 Varga I K

•Apr 14, 2019

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

Enjoyed very much and learnt even more.

创建者 Nadine A

•Dec 20, 2019

Challenging but excellent course, especially how content was organized and examples used to explain concepts

创建者 JIANG X

•Jun 30, 2019

Really thorough and in-depth material about statistical models with python.

创建者 Nicholas D

•Jan 23, 2020

Excellent course, really enjoyed the section on Bayesian statistics.

创建者 nipunjeet s g

•May 25, 2019

Very informative and the example

applications are extremely detailed

创建者 PRABAKARAN C

•Mar 17, 2020

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

创建者 Harish S

•Jan 27, 2019

Content of course was good. Some issue with quiz.

创建者 Appi

•Sep 24, 2019

Very good instructors and very good workload!

创建者 Debabrata A K S

•Feb 19, 2020

Very nice course. Well explained kudos.

创建者 Sumit M

•Mar 30, 2020

Very Very Good For learning Statistics

创建者 Jose H C

•Sep 02, 2019

It was good - Thanks.!

创建者 EDILSON S S O J

•Jun 18, 2019

Spectacular Course!

创建者 Kevin K

•Jan 02, 2020

Good Intro course

创建者 Gopichand M

•Mar 24, 2020

Excellent!

创建者 ILYA N

•Oct 05, 2019

The course is alright. They give a high-level overview of linear and logistic regression, and dip a little into Bayesian statistics.

Note that they use the StatsModel package in their practice assignments. So I was a bit disappointed I didn't get to practice sklearn, which is about x10 as popular in the field.